JPH0773013A - Data compressing method, data restoring method, and information processor - Google Patents

Abstract

PURPOSE:To provide a data compressing method, a data restoring method, and an information processor in which the compression rate is high and the restoration processing speed is high and only required characters are freely restored. CONSTITUTION:A dictionary is used where register data strings are registered in relation to register numbers, and two or more combinations of data strings are replaced with a pertinent register number to compress data. The dictionary is generated and updated in steps A1 and A2, and it is judged whether the dictionary is most suitable or not in a step A3. In this case, the dictionary is updated by the increment decomposition method, the additive increment decomposition method, or the like. When the most suitable dictionary is generated, the dictionary is outputted as the final static dictionary for restoration, and data is compressed by this static dictionary, and the compressed data string is outputted as the final compressed data for restoration in steps A4 and A5.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a data compression method using a dictionary in which a registration data string is registered in association with a registration number, a data recovery method for recovering compressed data, and an information processing apparatus.

[0002]

2. Description of the Related Art Recently, in information processing apparatuses such as printers, there is a demand to increase the added value by supplying bitmap fonts and outline fonts of various print sizes and to maintain high print quality at any print size. Is increasing. Therefore, in the field of printers and the like, recently, a data compression technique for efficiently storing a large amount of information composed of these font data has attracted attention.

As a conventional technique of data compression for storing or transferring a large amount of information with a capacity as small as possible, a technique of converting fixed-length bit data into a variable-length bit code such as Huffman code, or so-called Lempel- Z
iv The compression is performed by using the matching between the data string that has appeared in the past and the data string that is about to be compressed, such as the patent (US Pat. No. 4,464,650) and the LZW patent (US Pat. No. 4,558,302) Techniques are known.

However, these conventional techniques are data compression methods performed by using a so-called dynamic dictionary. That is, it is a method of analyzing target data to be compressed, registering the data in a dictionary structure while checking the appearance frequency, and simultaneously compressing the data using this dictionary. In this case, the feature of the dictionary is that it changes rapidly in real time.
In this data compression by the dynamic dictionary, only the target data that has been compressed remains as a product, but when restoring the data, the characteristics of the history data at the time of compression are checked, and the dictionary You have to restore the data. Therefore, there is a problem that the compressed target data must be processed sequentially from the beginning.

When compressing font data in a printer or the like, the compressed font data is stored in the printer or the storage device on the host computer side. Then, at the time of printing, necessary compressed font data is taken out from the storage device, and the compressed font data is restored to normal data to form print data. Therefore, when data compression is used under such conditions, what is needed is how quickly the data stored in the storage device is restored to form print data.

[0006] Another important point when compressing font data in a printer or the like is to have the flexibility to output any print data (character) in any order. That is, printers and the like are required to be able to randomly access stored data and form print data at random.

[0007]

[Problems to be Solved by the Invention] Lempel-Ziv and L, which are generally considered to have a higher compression rate than compression methods such as Huffman code
Data compression methods such as ZW are expected to become the mainstream of future compression technology. However, on the other hand, since these compression techniques use data compression using a dynamic dictionary, it is necessary to check and update the past data characteristics when restoring data, and it takes time to restore. There's a problem.

Further, in the data compression method such as Lempel-Ziv and LZW, at the time of decompression, the data must be decompressed in order from the beginning of the compressed data, and only necessary print data can be freely taken out when necessary. There is a problem that you can not.

In addition, in the data compression method called the incremental decomposition method used in LZW and the like, the number of data strings that can be registered in the dictionary can be increased only by one, so that, for example, when the same data string continues. Had a problem that the data compression rate could not be improved.

The present invention has been made to solve the above problems, and its purpose is to:
A data compression method, such as Lempel-Ziv or LZW data compression method, which maintains a high compression rate, yet can perform the decompression process in a relatively short time, and can freely decompress only the necessary data string. An object of the present invention is to provide a data restoration method and an information processing device capable of restoring a generated data string.

Further, another object of the present invention is to store a compressed data string and a dictionary generated at that time by creating a method having a higher compression rate than the incremental decomposition method. An object of the present invention is to provide a data compression method that can reduce the storage capacity, a data decompression method that can decompress a compressed data string, and an information processing device.

[0012]

In order to solve the above-mentioned problems, the invention of claim 1 uses a dictionary capable of registering a registration data string in association with a registration number and uses two or more combinations of data strings. A data compression method for compressing data by substituting a registration number. The dictionary is updated until the optimum dictionary for data compression of the data string to be compressed is generated, and when the optimum dictionary is generated, the dictionary is updated. The dictionary is output as a final static dictionary for decompression, the data string to be compressed is compressed by the static dictionary, and the compressed data string is output as final decompressed compressed data. It is characterized by

According to the invention of claim 1, a registration data string is registered in the dictionary in association with the registration number. And
Data compression is performed by replacing two or more combinations of data strings with the registration numbers. When the data compression is performed in this way, the original data string can be restored by reading the registered data string with the registration number at the time of decompression. In this case, the dictionary is updated until the optimal dictionary for data compression of the data string to be compressed is generated. That is, for example, the dictionary is updated until the amount of compressed data, the amount of dictionary data, and the like are optimized.
Then, when the optimum dictionary is generated, the dictionary is output as the final static dictionary for restoration. Further, the static dictionary performs data compression of the data string to be compressed, and the compressed data string is output as final compressed data for decompression. Then, the final static dictionary and compressed data that have been output are stored in, for example, a storage device, a storage medium, etc., and restored by an information processing device such as a printer or a computer, so that the original data string is restored. . As described above, according to the present invention, the dictionary is updated until the optimum dictionary is generated, and the static dictionary is used as the static dictionary to perform data compression by the static dictionary. Therefore, the data amounts of the static dictionary and the compressed data that are output can be optimized. Furthermore, since the dictionary until output does not have to be a static dictionary, it is possible to update and compress the dictionary with a data compression algorithm that uses a dynamic dictionary with a very high data compression rate. Become.
This makes it possible to greatly increase the data compression rate of the final compressed data. On the other hand, since the output dictionary becomes a static dictionary, it is possible to freely restore a necessary data string using this static dictionary.

According to a second aspect of the present invention, in the first aspect, the dictionary is updated until the optimal dictionary is generated by preferentially registering a combination of data strings having a large number of combinations. It is characterized in that registration of a registration data string that is used less frequently is deleted from the created dictionary until the number of registrations in the dictionary reaches a predetermined number.

According to the second aspect of the present invention, the dictionary is generated by preferentially registering the combinations of the data strings having a large number of combinations. As a method for generating such a dictionary, for example, a method called a slide dictionary can be used. When using this slide dictionary method, the longest matching data string between the past data string and the target data string is searched for by the slide dictionary method, and this longest matching data string is registered in the dictionary. Will create a dictionary. As a result, it is possible to generate a dictionary in which a combination of data strings having a large number of combinations is preferentially registered. By using such a dictionary, the combination of the data strings having a large number of combinations is preferentially replaced by the registration number of the dictionary, so that the data compression rate can be optimized. On the other hand, the dictionary generated in this way may have a very large number of registrations. Therefore, the dictionary is updated by deleting the registration of the registration data string that is rarely used from the generated dictionary, and the compression rate is good if the update is terminated when the number of registered dictionary reaches a predetermined number. In other words, it is possible to generate an optimal dictionary with a small amount of data.

According to the invention of claim 3, in claim 1, the update of the dictionary until the optimum dictionary is generated is performed by preferentially registering a combination of data strings having a high appearance probability. It is characterized in that registration of a registration data string that is used less frequently is deleted from the created dictionary until the number of registrations in the dictionary reaches a predetermined number.

According to the third aspect of the present invention, the dictionary is generated by preferentially registering a combination of data strings having a high appearance probability. The appearance probability of this combination of data strings can be obtained, for example, by examining the appearance probabilities of all data strings to be compressed, and from this appearance probability. By using the dictionary generated in this way, the combination of data strings having a high appearance probability is preferentially replaced with the registration number, so that the data compression rate can be optimized. Then, the dictionary is updated by deleting the registration of the infrequently used registration data string from the generated dictionary, and if the update is terminated when the number of registered dictionary reaches a predetermined number, the optimal amount of data is optimized. It is possible to generate a different dictionary.

According to a fourth aspect of the present invention, in the first aspect, the dictionary is updated by the data compression algorithm in which the dictionary dynamically changes during data compression until the optimum dictionary is generated. While performing the data compression process on all the data strings to be compressed, and using the dictionary updated by the process to update the dictionary again by the data compression algorithm for all the data strings to be compressed. It is characterized in that a data compression process is performed and the above process is repeated until the data compression rate becomes optimum.

According to the fourth aspect of the invention, the data for all the data strings to be compressed is updated while updating the dictionary by a data compression algorithm in which the dictionary dynamically changes at the time of data compression, such as an incremental decomposition algorithm or an incremental decomposition algorithm. The compression process is performed. Then, while the dictionary updated by this process is used to update the dictionary again by the data compression algorithm, the data compression process is performed on all the compression target data strings. Then, this process is repeated until the data compression becomes optimum, so that the optimum dictionary is generated. According to the present invention, data compression is performed by a data compression algorithm that uses a dynamic dictionary with a high data compression rate, and the dictionary is updated at the stage where the data compression rate is optimum, so the data compression rate is greatly increased. It becomes possible. On the other hand, since the output dictionary becomes a static dictionary, it is possible to freely restore a necessary data string using this static dictionary.

Further, the invention of claim 5 is a data compression method for performing data compression by using a dictionary capable of registering a registration data string in association with a registration number and replacing two or more combinations of data strings with the registration number. And (A) a step of extracting a predetermined number of data strings from the data string to be compressed and storing them in a work area having a predetermined number of buffers;
(B) It is analyzed whether or not a combination of data strings stored in adjacent buffers in the work area is registered in the dictionary, and if the combination is registered in the dictionary, the combination of the data strings in the dictionary is analyzed. The data string is shifted in the work area so as to fill the empty buffer created by the replacement as well as the registration number, and as a result, the subsequent data string is fetched in the empty buffer created at the end of the work area, and again in the working area. A step of analyzing whether or not a combination of data strings stored in the adjacent buffers is registered in the dictionary, and (C) a data string stored in the adjacent buffers in the work area by the analysis of the step (B). If it is determined that none of the combinations of are registered in the dictionary, they are stored in the first and second buffers from the beginning in the work area. The combination of the data strings to be registered is registered in the dictionary, the first data string is deleted, the data string is shifted in the work area so as to fill the empty buffer created by the deletion, and as a result, the empty space created at the end of the work area A step of fetching a subsequent data string in the buffer, and repeating the steps (B) and (C) until all the data strings to be compressed are stored in the working area.

According to the invention of claim 5, it is analyzed whether or not the combination of the data strings stored in the adjacent buffers in the work area is registered in the dictionary, and if registered, the dictionary is registered. Will be replaced by a number. Then, the subsequent data string is fetched into the resulting empty buffer, and it is analyzed again whether or not the combination of the data strings is registered in the dictionary. Then, when it is determined that the combination of the data strings is not registered in the dictionary, the combination of the first and second data strings from the beginning is registered, and the subsequent data string is loaded into the resulting empty buffer. Data compression is performed by repeating these processes until all the data strings are stored in the work area. As described above, according to the present invention, the work area having the predetermined capacity is provided, and when the same data row as the data row of interest exists in the work area, the replacement process using the dictionary is performed. There is. Therefore, particularly when the same data string is compressed, the number of registered dictionaries can be made extremely smaller than that of the conventional incremental decomposition method, and the dictionaries are replaced by the registered numbers of the dictionaries and compressed. The compressed data itself can have a very small data amount as compared with the conventional incremental decomposition method.

According to the invention of claim 6, in claim 5, the steps (B) and (C) are repeated once until all the data strings to be compressed are processed. A data compression method for compressing data in the current path using the dictionary updated in the previous path when the path is used, and the step (B) in the current path,
If the number of repetitions in (C) is less than or equal to the number of repetitions in the previous pass, the process moves to the next pass, and the number of repetitions in steps (B) and (C) in the current pass is greater than the number of repetitions in the previous pass. If it is larger, the dictionary updated in the previous pass is output as the final static dictionary for decompression, and the static dictionary compresses the data in one pass to obtain the final compressed data string. It is output as compressed data for various decompression.

According to the sixth aspect of the present invention, it is judged whether or not the data compression rate has become optimum by comparing the number of times the process is repeated in the current pass with the number of times the process is performed in the previous pass. Then, when the optimum data compression rate is reached, the dictionary is set as the final static dictionary, and the static dictionary and the data compressed by the static dictionary are output. Therefore, the data compression is possible by the additive decomposition algorithm with a very high compression rate, and the data compression rate is greatly improved, and the output dictionary becomes a static dictionary. It is also possible to restore freely.

Further, the invention of claim 7 is based on claims 1 to 6.
In any one of the above items, the dictionary stores the registration number and the registration data string as well as the usage frequency information, and includes the step of sequentially deleting the registration data string having a low usage frequency.

According to the invention of claim 7, there is included a step of sequentially deleting the registrations of the registration data string which is not frequently used. Therefore, when there is a limit to the number of dictionaries that can be registered, the data amount of the dictionaries can be set to the optimum size.

Further, in the invention of claim 8, in claim 7, the deletion of the registration data string having a low frequency of use gradually reduces the number of times of use of the registration data string registered in the dictionary. It is characterized in that it is performed by preferentially deleting a registered data string whose frequency of use has become a predetermined number or less.

According to the invention of claim 8, the number of frequencies of use of the registered data string registered in the dictionary is gradually reduced,
Initially, the registered data sequence in which the frequency of use has become equal to or less than the predetermined number is preferentially deleted. As a result, when the number of dictionaries that can be registered is limited, the amount of data in the dictionary can be optimized. In addition, since the registered data string whose usage frequency has become equal to or less than the predetermined number is preferentially deleted, it is possible to leave the registered data string having a high usage frequency in the dictionary and generate an optimal dictionary.

Further, the invention of claim 9 relates to claims 1 to 8.
In any of the above, the data string to be compressed is the font data necessary for printing characters.

According to the ninth aspect of the invention, the font data required for character printing is to be compressed. As such font data, bitmap font data,
Outline font data, etc. can be considered. When compressing bitmap font data, for example, a predetermined number of units arranged in the vertical direction and the horizontal direction (for example, 1 byte unit,
The dot data of 1 word unit) can be the compression target. Further, when the outline font data is compressed, for example, attribute information of each point forming the outline of the character, information for controlling vector coordinates of each point, or the like can be a compression target.

Further, in the invention of claim 10, in claim 9, only a part of the font data is a data string to be compressed, and the other part is data compressed by another data compression method. It is characterized by being done.

According to the tenth aspect of the present invention, a part of the data is compressed by a data compression method using a static dictionary, an incremental decomposition algorithm, an incremental decomposition algorithm, etc., according to the characteristics of the data forming the font data. , The other part is compressed by another compression method, for example, the Huffman coding method. In this way, by changing the compression method to be applied according to the characteristics of the data, it is possible to further increase the data compression rate.

The invention of claim 11 is characterized in that in any one of claims 9 and 10, data compression is performed for the characters having a common font by using the common dictionary. .

According to the eleventh aspect of the present invention, data compression is performed for characters having a common font using a common dictionary. For example, for the characters in Mincho type, all the dictionaries dedicated to Mincho type are used to update the dictionary and compress the data to obtain the final static dictionary and compressed data. For Gothic character strings, a dictionary dedicated to Gothic is used for all dictionary updates and data compression to obtain the final static dictionary and compressed data. By using a common dictionary for each font in this way, data can be efficiently compressed.

The invention of claim 12 is characterized in that, in any of claims 1 to 8, the data string to be compressed is a character string.

According to the twelfth aspect of the invention, the character string data is to be compressed. As a result, it is possible to save, for example, the capacity required for storing characters.

According to the thirteenth aspect of the present invention, in any one of the first to twelfth aspects, the registration data string is exclusively used for restoration from the registration number and the information of the registration data string included in the finally generated dictionary. A restore-only dictionary is generated that includes the restore-only registered data string converted into the data format of, the data length of the restore-only registered data string, and the start address information of the restore-only registered data string.

According to the thirteenth aspect of the present invention, the restore-only registration data string, the data length of this restore-only registration data string,
A restoration-only dictionary including the start address information of the restoration-only registration data string is generated. Then, at the time of restoration, the restoration of data is performed using this restoration dedicated dictionary. That is, by reading the restoration-dedicated registration data string having the length designated by the data length from the position designated by the start address, the data is read from the dictionary and the restoration processing is performed. In this case, the restore-only registration data string is converted into a restore-only data format. Therefore, the restoration process can be performed much faster than when using a normal dictionary.

According to a fourteenth aspect of the present invention, the compressed data generated by the data compression method according to any one of the first to thirteenth aspects and the final dictionary are used to perform decompression processing according to the data compression method. The feature is that the data string that is the compression target is restored.

According to the fourteenth aspect of the present invention, the original data string is restored using the compressed data generated by the above data compression method and the final dictionary. As a result, it is possible to perform a predetermined process, for example, a process such as character printing, using this restored data string.

According to a fifteenth aspect of the present invention, the compressed data generated by the data compression method according to any one of the first to thirteenth aspects and the final dictionary are used to perform decompression processing according to the data compression method. It is characterized in that it includes means for decompressing a data string that is a compression target.

According to the fifteenth aspect of the present invention, the original data string is restored by the restoring means by using the compressed data generated by the data compression method and the final dictionary. The restoring means can be incorporated in an information processing device such as a computer or a printer.

[0042]

EXAMPLES The best examples of the present invention will be described below. In addition, in the following first and second embodiments, a case where a character string is mainly compressed as a data string is described as an example for the sake of simplicity. However, the data string in the present invention includes not only such a character string but also any kind of data string such as a byte string and a word string for forming font data.

1. First Embodiment FIG. 1 shows a flowchart for explaining the data compression method of this embodiment. In the data compression method of this embodiment, a dictionary that can register a registration data string in association with a registration number is used. Then, data compression is performed by replacing two or more combinations of data strings with this registration number. First, a dictionary is generated from all the data strings (for example, character strings) to be compressed (step A
1) The dictionary update is repeated until the optimum dictionary for data compression is generated (steps A2 and A3). And
When the optimum dictionary is generated, this dictionary is used as the final static dictionary for decompression, and the data string to be compressed is compressed by this static dictionary (step A4). Then, the compressed data for final decompression and the static dictionary for final decompression that are thus compressed are output, and the mask R
It is stored in a storage device or storage medium such as OM and EEPROM. Then, using the static dictionary and the compressed data stored in this storage device or the like, data restoration processing is performed in an information processing device such as a printer or a host computer.

As a method of generating / updating a dictionary and deciding at which stage the dictionary is optimum for data compression, various methods can be considered as described later.

FIG. 2 shows an example of the configuration of the data compression device 12 in which the data compression method of this embodiment is used.
The entire data string 11 to be compressed is first input to the dictionary creating / updating means 13, and the dictionary is created / updated thereby. Then, when a dictionary optimal for data compression is generated, the dictionary is held in the static dictionary holding means 15 as the static dictionary 14. Then, the held optimum static dictionary 14 is output to the external storage means (not shown) by the static dictionary output means 16 while the data compression means 1 is output.
7 is used for data compression of the entire data string 11. This data compression is performed by replacing two or more combinations of data strings with registration numbers in the dictionary. Then, the compressed data 19 obtained as a result is output to the external storage means by the compressed data output means 18.

Next, the structure of the dictionary in this embodiment will be described. For example, "static_string_dictionar
Consider a case where a data string (character string) "y" is compressed. In this case, "st", "at", "ic", "_", "st", "
Assume that a combination of eight data strings such as "ring_d", "ic", and "tionary" has been registered. In this case, the combination of these data strings is associated with a registration number as shown below, for example. Registered: 0: st 1: at 2: ic 3 :: 4: ring_d 5: tionary Then, "static_string_dictio"
The data string "nary" can be replaced by 0, 1, 2, 3, 0, 4, 2, 5 by these registration numbers, and the data is compressed by this.

Next, various techniques for generating an optimum dictionary will be described. In this embodiment, finally, two of the static dictionary and the compressed data are output, and these are stored in the storage device. Therefore, in order to save the used capacity of the storage device, it is necessary to reduce the data amount of the final static dictionary and compressed data, and a dictionary that can reduce the data amount can be called an optimum dictionary. That is, in order to obtain an optimal dictionary, it is desirable that the data amount of the dictionary itself can be reduced, or that the compressed data amount can be reduced. Therefore, in this embodiment, for example, the following first to fourth methods are used. In the following, a character string will be described as an example of the data string.

(A) First Method for Obtaining Optimal Dictionary In this method, a method called a slide dictionary is used, and a dictionary is generated by preferentially registering combinations of data strings having a large number of combinations. . Then, the optimum dictionary is obtained by sequentially deleting the number of created dictionary registrations based on the usage frequency information.

First, a method called a slide dictionary will be described with reference to FIGS. In this method, all the character strings 41 to be compressed are targeted for the target character string 4 in order from the beginning.
3 is stored in the memory space which is the work area. Then, the past character string 42 (target character string 4 from the beginning
It is checked whether there is no same character string as the target character string 43 before 3). If there is no same character string in the past, the first character of the target character string 43 is replaced with the target character string 43.
To the past character string 42 (slide). On the other hand, if there is the same character string in the past, it is checked whether the next character string also matches, and by repeating this, the longest matching character string (character string between the past character string 42 and the target character string 43 (character string The one with the largest number of combinations).

For example, if the character string to be compressed is ABCA
Consider the case of BCDEF. In this case, first A
Becomes the target character string 43, but since there is no same character string in the past, A is moved to the slide dictionary which is the past character string 42 (see FIG. 3B). Since B and C do not have the same character string in the past, they are moved to the slide dictionary (FIG. 3).
(See (C)). Then, A becomes the target character string 43 next. In this case, since A is in the slide dictionary, it is checked whether the next B matches (see FIG. 3D).
Then, in this case, since they match, whether or not C matches next is checked (see FIG. 3E). And then D
Are checked for a match, but D is not in the slide dictionary. Therefore, in this case, ABC is the longest matching character string.

Now, in the method called slide dictionary,
In this way, by finding the longest matching character string ABC, for example, the character string ABCABCDDEF is "A",
"B", "C", "the same as the last three characters", "D",
Compress to “E” and “F.” Specifically, when there is no match, the character string is represented by “no match flag = 1 and its character code”, and when there is a match, Data compression is performed by representing the longest match character string with "no match flag = 0, match location, and match length".

However, in the present embodiment, the slide dictionary method is not used for actual data compression, but
It is used only to find the longest matching string in the string to be compressed. In this embodiment, when the longest matching character string is found, the longest matching character string is registered in the dictionary in association with the registration number. In the above example, ABC
Will be registered in the dictionary. In this way, the longest matching character that appears twice or more in all the compression target character strings is found, and these are registered in the dictionary.
As a result, a character string having a large number of combinations will be preferentially registered in the dictionary.

When the slide dictionary method is used, it is necessary to store past character strings in the memory. However, as shown in FIG. 3A, the capacity of the memory is finite and the range that can be stored in the memory is finite. Therefore, in this case, only the past character string 42 within the range that can be stored in the memory becomes the slide dictionary.

FIG. 4 shows a flowchart for explaining a method for obtaining an optimum dictionary by using the slide dictionary method. As shown in FIG. 4, the longest matching character that appears twice or more in the compression target character string is first found by using the slide dictionary method, and the dictionary is created by registering these in the dictionary (step B1). ). Next, using the generated dictionary, find a combination of the dictionary registration character string and the longest matching character string from all the compression target character strings,
When found, the frequency of use of the registered character string is increased by one (step B2). For example, the compression target character string is A
In BCDEF, when the registered character strings are AB and ABC, the frequency of use of the registered character string ABC is increased by one.

After the frequency of use is calculated in this manner, the registered character string with the lowest frequency of use is next calculated, for example, 100.
The registration of about individual items is deleted (step B3). in this case,
For example, the number that can be registered in the dictionary is 4096-256 = 38.
If the number is 40, the registration is deleted so that the total number of registrations does not fall below 3840. Specifically, for example, when the total number of registrations in the dictionary before deletion is 3,900, only 60 are deleted.

Next, the total number of registrations is 3840 (predetermined number).
It is determined whether or not the number is below (step B4). If the number is more than 3840, the process returns to step B2, the usage frequency is calculated again, and about 100 registrations are deleted at step B3. In this way, steps B2 to B4 are repeated, and the number of registered dictionary is gradually decreased little by little. Then, when the number of registrations reaches 3840, the process proceeds to step B5. Since, for example, 3840 can be registered in the dictionary as described above, when the number of registrations reaches 3840, the dictionary becomes an optimum dictionary.

Finally, this optimal dictionary is used as a static dictionary, all the character strings to be compressed are compressed by this static dictionary, and the final static dictionary and compressed data are output (step B5, B6).

(B) Second Method for Obtaining Optimal Dictionary In this method, a dictionary is generated by preferentially registering a combination of character strings having a high appearance probability. Then, the optimum dictionary is obtained by sequentially deleting the number of created dictionary registrations based on the usage frequency information.

First, all character strings to be compressed are, for example, 1
The occurrence probability of each character string is calculated by performing analysis twice. Then, based on this appearance probability, the appearance probability of the combination of character strings is obtained.

For example, by the above analysis / calculation, a,
It is assumed that the appearance probabilities of b, c, and d are obtained as a; 50% b; 20% c; 10% d; 5%. Then, the occurrence probability of the combination aa of the character strings is: aa; 25% aaa; 12.5% ab; 10% ba; 10% ac; 5% ca; 5% aab; 5% aba; 5% baa; 5 % Ad; 2.5% is calculated. However, this is an expected value when it is assumed that there is no correlation between the appearance probabilities between the character strings.

In this way, after obtaining the appearance probabilities of the character string combinations, the dictionary is generated by preferentially registering the character string combinations having the high appearance probability. Next, for example, by a method similar to steps B2 to B4 of FIG. 4, the registration of the character string that is less frequently used is deleted until the predetermined number of dictionary registrations, for example 3840, are generated, and an optimum dictionary is generated. Then, the final static dictionary and the compressed data compressed thereby are output by the same method as in steps B5 and B6. According to the above method, there is an advantage that the first analysis can be completed by one scanning.

(C) Third Method for Obtaining Optimal Dictionary In this method, an optimal dictionary is obtained by using an incremental decomposition algorithm. For more information on the incremental decomposition algorithm,
This will be described in comparison with the additive decomposition algorithm in the second embodiment described later.

FIG. 5 is a flow chart for explaining a method of obtaining an optimum dictionary by using the incremental decomposition algorithm. In this method, first, the dictionary is initialized (step C1). With this, the dictionary registration number 0
The registration character string is registered only in 255. Specifically, the ASCII code characters are stored in 0 to 255. Next, NUM0, which represents the number of times compressed data is output, is NU.
It is set to M0 = 0 (step C2). Then, the dictionary is updated using the incremental decomposition algorithm to perform data compression on all the compression target character strings, and when the compressed data should be output, the value of NUM0 is incremented by 1 (step C3). At this time, the compressed data itself is not output to the outside. This is because the processing in step C3 is intended for updating the dictionary.

Next, NUM1 is set to NUM1 = 0 (step C4). After that, the same processing as in step C3 is performed using the dictionary finally obtained in step C3. That is, data compression is performed on all compression target character strings while updating the dictionary using the incremental decomposition algorithm, and when the compressed data is to be output, the value of NUM1 is incremented by 1 (step C5). Also in this case, the compressed data itself is not output to the outside.

Next, it is determined whether or not NUM1> NUM0 (step C6). As a result, it is determined whether or not the data compression rate has been optimized by the processing of step C5, that is, whether or not the dictionary has been optimized. And NUM1 ≦
If it is NUM0, it is not the best dictionary yet, and NU
M0 = NUM1 is set (step C7), and step C
The processes of 4 and C5 are repeated. NUM0 and NUM1 represent the number of times the compressed data is output, and a small number thereof means that the data amount of the compressed data is also small. Therefore, NUM1 ≦ NUM0 means that the data compression rate is improved in the process of step C5. Therefore, in this case, the processes of steps C4 and C5 are repeated. And step C
If NUM1> NUM0 in step 6, it is determined that the dictionary is optimal for data compression.

Next, this optimal dictionary is set as a static dictionary,
All the compression target character strings are compressed by this static dictionary (step C8). However, the dictionary is not updated during this data compression. Then, finally, the final static dictionary and the compressed data thus compressed are output (step C9).

FIG. 6 shows a visual representation of the above processing. All the compression target character strings 21 are first analyzed, and a temporary dictionary 22 is created by this (this dictionary is a dynamic dictionary). Next, the entire compression target character string 21 is again subjected to the second analysis, and the dictionary 23 of the updated version 1
Is created. Further, similarly, the dictionary 24 of the updated version 2 is created. In this way, the dictionary is repeatedly updated, and when the data compression rate is determined and the optimum dictionary is obtained, this is set as the final static dictionary 25. Then, the static dictionary 25 is used to compress all the compression target character strings 21 again.
However, at this time, the static dictionary 25 remains static,
The dictionary is not updated. Then, the static dictionary 25 and the compressed data are output to the outside and stored in the storage device.

The main differences between the method shown in FIGS. 5 and 6 and LZW are as follows. That is, in LZW, only compressed data is finally output as a product after data compression, and the dictionary is a dynamic dictionary and is not output. LZ
W is a data compression method used for data communication through a telephone line. The transmission side outputs compressed data by LZW, and the reception side restores it. At the time of this restoration, it is necessary to analyze the characteristics of the compressed data and restore the data while recreating the dynamic dictionary from the compressed data. Therefore, the compressed data must be processed sequentially from the beginning, the restoration speed is slow, and a required data string cannot be randomly accessed and restored. Therefore, it is difficult to use the data compressed by LZW for font data of a printer or the like.

On the other hand, in the method shown in FIGS. 5 and 6, unlike LZW, finally, two data, compressed data and static dictionary, are output. Therefore, even when data is restored, there is no need to recreate the dictionary, so the restoration speed is high. Further, since the static dictionary is used, it is possible to randomly access a desired data string in the compressed data. In addition, the advantage that the restoration speed is fast and the data string can be randomly accessed is obtained not only by the third method but also by the first and second methods described above and the fourth method described later. This is an advantage.

(D) Fourth Method for Obtaining Optimal Dictionary In this method, the optimal dictionary is obtained using the additive decomposition algorithm. The additive decomposition algorithm will be described in detail in the second embodiment. However, the flow of the process itself is almost the same as that of FIG. 5 except that the data compression in steps C3 and C5 is performed by the additive decomposition algorithm.

In the third method described above, since the data is compressed using the incremental decomposition algorithm, compressed data with a high compression rate can be obtained, but since there is a step of registering each character, the processing speed is high. It is by no means fast, and the compression ratio is not high compared to the additive decomposition algorithm. Therefore, when increasing the compression rate, it is desirable to adopt the fourth method using this additive decomposition algorithm.

In the above first to fourth methods,
The compressed data is output as a fixed bit length code.
This code is, for example, 12 bits or 1 word of 16 bits. And 16-bit 1
The word has a merit that the processing speed is improved, but has a demerit that the compression rate is lower than that of the case of 12 bits.

As described above, according to the present embodiment, in order to create the optimum static dictionary, it is necessary to delete the dictionary registration based on the frequency of use or scan the data a plurality of times during compression. Processing time becomes longer. However, this is not a problem for the user. In other words, the compression process is necessary when writing data to, for example, a non-rewritable storage device or storage medium (ROM, etc.), which has no effect on the processing time at the time of restoration after compression. Because not. Specifically, when a user prints using a printer equipped with a storage medium that stores data compressed by the compression method, it takes a lot of time for the manufacturer to create the compressed data, but the user prints the compressed data. This is because the speed of the restoration process that is performed when it is desired to perform is not particularly slow.

2. Second Embodiment (A) Additive Decomposition Method FIG. 7 is a diagram schematically illustrating a data compression method (hereinafter referred to as an additive decomposition method or an additive decomposition algorithm) used in the second embodiment. Shown.

The character string data 1 to be compressed is first stored in the work buffer 2 which is the work storage means from the first portion of the data. Next, it is compared whether the character string registered in the dictionary 3 does not exist among the character strings in the working buffer 2, and if there is, the information in the dictionary 3 is updated and the character string in the working buffer 2 is updated. The character string is replaced with the registration number, and the next target character string is added to the work buffer 2. On the other hand, if there is no registered character string, the first two characters in the work buffer 2 are registered in the dictionary 3,
The first character is output as compressed data 4. And
The next target character string is added to the work buffer 2, and it is again compared whether or not the character string in the work buffer 2 registered in the dictionary 3 exists. Data is compressed by repeating the above processing.

Next, the case where the following character string data is processed as a compression target by using the additive decomposition method to obtain a static dictionary and compressed data will be described in detail. Here, the character string data to be compressed is "ABCEBCHA, BBCCDCBCH, ABCABE".
HD, ABBCGABK ... ". However, here, it is assumed that ASCII code character data is registered in the numbers 0 to 255 of the dictionary composed of rewritable storage elements. Further, it is assumed that a buffer having a capacity of 16 bytes is prepared in the working storage means.

(1) First, data of the capacity of the working buffer (16 bytes) is fetched from the beginning of the character string data to be compressed. Then, the character string in the working buffer becomes "ABCEBCHA, BBCCBCH". Here, each character is numerical data represented by 1 byte, which follows the ASCII code table as described above. For example, "A" is 65, "B" is 66, and "C" is 67.

(2) Next, it is checked whether or not there is a character string (combination of character strings) of two or more characters already registered in the dictionary in this work buffer. However, since such a character string is not registered, for example 25
Register the first two characters "AB" at the 6th position as 2 (characters) in length, and 65 + 66 (ASCII code of "A" and "B") in the data field. Use once. In addition, the first character "A" in the work buffer
The registration number “65” of is output as compressed data and deleted in the work buffer. Then, all the subsequent character strings are shifted toward the beginning so as to fill the blank 1 byte in the work buffer generated by this, and the target character is stored in the resulting blank 1 byte at the end of the work buffer. "A" for one character is fetched from the continuation of the column data. Then, the character string in the working buffer is "BCEBCHAB, B
CCDBCHA ".

(3) Next, it is again checked whether or not there is a character string of two or more characters already registered in the dictionary in this work buffer. Then, working buffers 7 and 8
Since the character string "AB" exists in the first character, the character string "AB" for 2 bytes is replaced with 256 characters, and the usage frequency of the character string "256" in the dictionary is updated twice. To do. This replacement creates a blank space of 1 byte in the work buffer, so all the subsequent character strings are shifted toward the beginning so as to fill this blank space, and the resulting blank 1 byte at the end of the work buffer is the target. "B" for one character is fetched from the continuation of the character string data of. Then, the character string in the working buffer is "BCEBCH256B, CCDBCH
It becomes "AB".

(4) It is again checked whether or not there is a character string of two or more characters already registered in the dictionary in this work buffer. Then, since the character string "AB" exists in the 15th and 16th characters of the working buffer, the character string "AB" for 2 bytes is replaced with 256 characters, and "25" in the dictionary
Updates the frequency of use of the 6 "string to 3 times. This replacement creates a blank space of 1 byte in the working buffer. To fill this, shift all subsequent strings to the beginning, As a result, one character "C" is fetched from the continuation of the target character string data into the blank 1 byte at the end of the working buffer, and the character string in the working buffer becomes "BCEBCH256 B, CCDBCH256.
C ”.

(5) It is again checked whether or not there is a character string of two or more characters already registered in the dictionary in this work buffer. However, since such a character string has not been registered, the first two characters "B
C "is registered as 2 (characters) in length and 66 + 67 in the data field, and the frequency of use of this" 257 "is once. In addition, the first character in the work buffer is" The registration number "66" of B "is output as compressed data, erased in the work buffer, and all the subsequent character strings are moved toward the beginning so as to fill the empty 1 byte in the work buffer. The character string "A" from the continuation of the target character string data is fetched into the blank 1 byte at the end of the work buffer resulting from the shift, and the character string in the work buffer becomes "CEBCH256 BC, CDBCH256 CA. "
become.

(6) It is again checked whether or not there is a character string of two or more characters already registered in the dictionary in this work buffer. Then, since the character string of "BC" exists at the 3rd, 4th, 7th, 8th, and 11th and 12th characters of the working buffer, the character string of 6 bytes in total "
Replace "BC" with 257 characters each, "257" in the dictionary
Update the frequency of use of the string No. to 4 times. This replacement creates a 3-byte blank in the work buffer, so all the subsequent character strings are shifted toward the beginning so as to fill this space, and the resulting blank 3 bytes at the end of the work buffer are affected. "BEH" for 3 characters is taken in from the continuation of the character string data of. Then, the character string in the work buffer is "CE257 H256257CD, 257 H256 C
ABEH ”.

(7) It is again checked whether or not there is a character string of two or more characters already registered in the dictionary in this work buffer. Then, since the character string "AB" exists at the 13th and 14th characters of the working buffer, the character string "AB" of 2 bytes is replaced with 256 characters, and "25" of the dictionary is used.
Updates the frequency of use of the 6 "string to 4 times. This replacement creates a 1-byte blank in the working buffer. To fill this, shift all subsequent strings to the beginning, The resulting blank 1 byte at the end of the working buffer contains "D" for one character from the continuation of the target character string data, and the character string in the working buffer is "CE257 H256257CD, 257 H256 C25.
6 EHD ”.

(8) It is again checked whether or not there is a character string of two or more characters already registered in the dictionary in this work buffer. However, since such a character string is not registered, the first two characters "C
E "is registered as 2 (characters) in length and 67 + 69 in the data field, and the usage frequency of this" 258 "is once. In addition, the first character in the work buffer is" The registration number "67" of C "is output as compressed data, erased in the work buffer, and all the subsequent character strings are moved toward the beginning so as to fill the blank 1 byte in the work buffer. The character string "A" from the continuation of the target character string data is taken into the blank 1 byte at the end of the work buffer resulting from the shift, and the character string in the work buffer becomes "E257 H256257CD257, H256 C256. EH
DA ”.

(9) It is again checked whether or not there is a character string of two or more characters already registered in the dictionary in this work buffer. However, since such a character string is not registered, the first two characters "E
257 "is registered as 2 (characters) in length and 69 + 257 in the data field, and the usage frequency of this" 259 "is once. In addition, the first character in the work buffer is" The registration number "69" of E "is output as compressed data, erased in the work buffer, and all the subsequent character strings are moved toward the beginning so as to fill the blank 1 byte in the work buffer caused by this. The character string "B" is fetched from the continuation of the target character string data into the blank 1 byte at the end of the work buffer resulting from the shift, and the character string of the work buffer is "257 H256257CD257, H256 C256. EHD
It becomes "AB".

(10) It is again checked whether or not there is a character string of two or more characters already registered in the dictionary in this work buffer. Then, since the character string "AB" exists in the 15th and 16th characters of the working buffer, the character string "AB" for 2 bytes is replaced with 256 characters, and "2" in the dictionary is used.
Update the frequency of use of the 56 "string to 4 times. This replacement creates a 1-byte blank in the work buffer. To fill this, shift all the subsequent strings to the beginning, The resulting blank 1 byte at the end of the working buffer is "B" for one character from the continuation of the target character string data.Then, the character string in the working buffer is "257 H256257CD257, H256 C256 E
HD256 B ”.

(11) It is again checked whether or not there is a character string of two or more characters already registered in the dictionary in this work buffer. However, since such a character string is not registered, the first two characters "2
57H "is registered as 2 (characters) in length and 257 + 72 in the data field, and the usage frequency of this" 260 "is once. Furthermore, the first character in the work buffer is" Outputs "257" as compressed data, erases it in the work buffer, shifts all subsequent character strings toward the beginning so as to fill the blank 1 byte in the work buffer, which results One character "C" from the continuation of the target character string data in the blank 1 byte at the end of the work buffer
Take in. Then, the character string in the working buffer is "H25
6257CD257 H, 256 C256 EHD256 BC ”.

(12) It is again checked whether or not there is a character string of two or more characters already registered in the dictionary in this work buffer. Then, since the character string of "257H" exists in the 7th and 8th characters of the working buffer and the character string of "BC" exists in the 15th and 16th characters, respectively, the character string of 4 bytes in total. 257H "is replaced with 260, and" BC "is replaced with 257, and the frequency of use of" 260 "in the dictionary is updated twice and the frequency of use of" 257 "is updated five times. This replacement creates a 2-byte blank in the work buffer, so all the subsequent character strings are shifted toward the beginning so as to fill this blank space, and the resulting blank 2 bytes at the end of the work buffer are affected. "GA" for 2 characters is taken in from the continuation of the character string data of. Then, the character string in the work buffer is "H256257".
CD260256C, 256 EHD256257GA ".

(13) It is again checked whether or not there is a character string of two or more characters already registered in the dictionary in this work buffer. However, since such a character string is not registered, the first two characters "
H256 "is registered as 3 (characters) in length and 72 + 256 in the data field, and the usage frequency of this" 261 "is once. Furthermore, the first character in the work buffer" The registration number "72" of H "is output as compressed data, erased in the work buffer, and all the subsequent character strings are moved toward the beginning so as to fill the blank 1 byte in the work buffer. The character string "B" is fetched from the continuation of the target character string data into the blank 1 byte at the end of the work buffer resulting from the shift.
B ”.

(14) It is again checked whether or not there is a character string of two or more characters already registered in the dictionary in this work buffer. However, since such a character string is not registered, the first two characters "2
56257 ", length is 4 (characters), data field is 256 + 257
, And the usage frequency of this "262" is once.
In addition, the first character "256" in the work buffer is output as compressed data, erased in the work buffer, and the subsequent characters are filled so as to fill the empty 1 byte in the work buffer. All columns are shifted toward the beginning, and the resulting blank 1 byte at the end of the work buffer is one character "K" from the continuation of the target character string data.
Take in. Then, the character string of the work buffer is "257
CD260256C256 E, HD256257GABK ".

(15) It is again checked whether or not there is a character string of two or more characters already registered in the dictionary in this work buffer. Then, since the character string "256257" exists in the 11th and 12th characters of the work buffer, the "256257"
Replaces 262 with 262 and updates the dictionary "262" usage frequency to twice. This replacement creates a blank space of 1 byte in the work buffer, so all the subsequent character strings are shifted toward the beginning so as to fill this blank space, and the resulting blank 1 byte at the end of the work buffer is the target. 1 character is fetched from the continuation of the character string data of. Then, the character string in the working buffer is "257 CD260256C256 E, HD
262 GABK. "

As described above, according to the additive decomposition method of this embodiment, data is sequentially fetched from the character string data to be compressed so that the length of the character string in the working buffer is always kept constant. Then, if a combination of adjacent character strings from the beginning in the work buffer is registered in the dictionary, this is replaced with the registration number of the dictionary to perform compression. Further, if this combination of character strings is contained in the work buffer, it is also replaced with the registration number of the dictionary to perform further compression. Therefore,
The data amount of the compressed data is reduced as compared with the case of the conventional incremental decomposition method, and as a result, the compressed data can be stored with a small storage capacity. It should be noted that the compressed data will be output after the combination of the character strings is registered in the dictionary when the combination of the adjacent character strings from the beginning in the work buffer is not registered in the dictionary.

The above processing is schematically shown using a tree structure as shown in FIG. In FIG. 8 (A), the numbers are assigned according to (1) to (15) used in the above description. However, (1), (10), (12), (1
5) is not shown in FIG.

For example, the step (2) of registering "AB" in the dictionary and outputting "A" is expressed as follows in FIG. 8A. That is, in FIG. 8A, the dictionary registration is expressed by setting "AB" at the tip of the up arrow. Also, the character "A" is added to the end of the down arrow to express that the character is output as compressed data. Further, by adding a process number "2" near these up and down arrows, it is expressed that the process is the process (2).

When the character "AB" registered in the dictionary is found in the work buffer and replaced by the registration number as in the step (3) above, the character string to be replaced is grouped over the character string to be replaced. , The process number "3" is added to the process.

Incidentally, in the case of the present embodiment, the compressed output data is as follows. "A, B, C, E, 257, H, 256, 257, C, ...
.. Also, the following character strings will be registered in the dictionary. 0 to 255 ASCII code 256 AB 257 BC 258 CE 259 E257 260 257 H 261 H256 262 256 257 (B) Incremental decomposition method Next, the same character string data as the above example is converted into the conventional incremental decomposition method. A case where the dictionary and the compressed data are obtained by processing by the method using is described. However, here again, it is assumed that the ASCII code characters 0 to 255 are registered in the dictionary from the beginning. "ABCEBCHA, BBCCDBCH, ABCABE
HD, ABBCGABK ... "(1) The character string sent is not once stored in the work buffer in fixed bytes, as in the additive decomposition method described above, but the minimum required for the beginning part. Only the character string of is taken into the working buffer. Therefore, it is checked whether or not the first character "A" in this work buffer is registered in the dictionary. Then, since the "A" is registered at the 65th position in the dictionary, the count number of its use frequency is set to 1.

(2) Next, the second character "B" is added, and it is checked whether or not the character "AB" in this work buffer is registered in the dictionary. However, a character string of two or more characters already registered in the dictionary cannot be found. Therefore, the first two characters "AB" are registered in the 256th position of the number, the length is 2 (characters), and 65 + 66 is registered in the data field, and the usage frequency of "256" in the dictionary is described as once. Next, the leading "A" in the working buffer is output as compressed data, and next, attention is paid to the second character "B" of the target character string data.

(3) Check if the new first character "B" is registered in the dictionary. Then, since the "B" is registered at the 66th position in the dictionary, the count number of its use frequency is set to 1.

(4) Next, a new second character "C" is added to check whether or not the character "BC" in this working buffer is registered in the dictionary. However, a character string that is already registered in the dictionary with a character string of two or more characters cannot be found. Therefore, the first two characters "BC" are registered as the 257th number, the length is 2 (characters), and 66 + 67 is registered in the data field, and the usage frequency of "257" in the dictionary is once. next,
The leading "B" in the work buffer is output as compressed data, and next, attention is paid from the third character "C" of the target character string data.

(5) Whether the same operation as above continues from the beginning up to the fourth character E, "EB" is registered, and then the new first character "B" in the working buffer is registered in the dictionary. Find out. However, since the "B" is registered at the 66th position in the dictionary, the count number of its use frequency is set to 2 this time.

(6) Next, a new second character "C" is added to check whether or not the character string "BC" in this working buffer is registered in the dictionary. Then, since the character "BC" is registered at the "257" th position in the dictionary,
The frequency of use is described as twice, and it is checked whether or not the character string "BCH" to which a new third character is added is registered in the dictionary.

(7) Then, this is not registered, so register this 2 character string "BCH" as the 260th number, the length is 3 (characters), and 257 + 72 in the data field, The usage frequency of "260" in the dictionary is described as once. Next, at the beginning "B
The registration number "257" of C "is output as compressed data, and next, attention is given to the seventh character" H "of the target character string data.

FIG. 9 shows, as a reference, a flow chart for explaining the operation of the above incremental decomposition method.

Although the incremental decomposition method is performed in this way, the major difference from the incremental decomposition method of the present embodiment is that the character string data to be processed is fetched one character at a time from the beginning, and the agreement with the dictionary is checked. Is to go.

The above processing is schematically shown in FIG. 8B using a tree structure as in the example of FIG. 8A. However, the numbers 1 to 8 in the figure do not follow the numbers used in the above description of the steps. Here, for example,
In the first step of registering "AB" in the dictionary and outputting "A",
The word "AB" at the tip of the up arrow indicates dictionary registration, and the character "A" at the tip of the down arrow indicates that the character is output as compressed data.

Now, as can be understood from FIG. 8 (B),
In the conventional incremental decomposition method, the character "AB" registered in the dictionary is found somewhere other than the beginning in the working buffer and replaced with the registration number, as in step (3) of FIG. 8A. There can be no process. All that is possible is to add a new character to the right side of the character string registered in the dictionary and wrap it up to create a new character string, as in step 5 of FIG. 8 (B). .

Incidentally, the compressed output data by this incremental decomposition method is as follows. "A, B, C, E, 257, H, 256, 257, C, D, 25
7, H, 256, ... ”In addition, the following character strings are eventually registered in the dictionary. 0 to 255 ASCII code 256 AB 257 BC 258 CE 259 EB 260 257 H 261 HA 262 256 B 263 257 C 264 CD 265 DB 266 260 A ... When comparing FIG. 8 (A) and FIG. 8 (B) , In the range shown in the example, the output compressed data is the same,
The character strings registered in the dictionary are definitely different, and the more the target character string goes after the character string data to be compressed, the more different the character string becomes.

As described above, since the conventional incremental decomposition method can increase only one character at a time, in particular, as shown in FIG.
Regarding character string data in which the same character string is continuous as shown in (B), there is a big difference from the additive decomposition method of the present embodiment, and the additive decomposition method can be stored with a smaller storage capacity. .

FIG. 10A shows the case where a continuous character string is compressed by the additive decomposition method of this embodiment.
(B) shows a case where consecutive character strings are compressed by the incremental decomposition method. In the case of the incremental decomposition method of FIG. 10 (B), the dictionary contains A, AA, AAA, AAAA, AAAAA, AA.
Since registration is performed in the order of AAAA, ...
To compress 16 bytes, 16 outputs and 17 dictionary entries must be done. On the other hand, in the case of the additive decomposition method of this embodiment shown in FIG. 10A, the dictionary contains A, AA, and AAA.
A, AAAAAAAA, AAAAAAAAAAAAAAA
Since the registration is performed in the order of AA, ..., Only the output of 5 times and the dictionary registration of 6 times are required to compress the 16-byte character of A.

As described above, in the case of character string data in which the same characters are continuous, the effect of the additive decomposition method of this embodiment is clear, and the compression rate thereof is much higher than that of the conventional incremental decomposition method. In other words, this means that the same number of output times is required to process the same amount of character string data. Since the character string at the time of output is always replaced with the fixed length byte of the registration number of the dictionary and is output, the small number of times of output indicates a small number of bytes, which means that the compressed data is small.

(C) Generation of Optimal Dictionary Like the above-mentioned FIG. 6, the processing by the additive decomposition method described above is performed a plurality of times for all character strings to be compressed, which makes the character string data most efficient. The optimal dictionary that can be compressed well is generated. The dictionary optimization process will be described below with reference to FIGS. 11 and 12.

The flow chart of FIG. 11 shows the processing of one pass performed by the additive decomposition method for optimizing the dictionary. Here, one pass means that all the character strings are stored in the work buffer and all the character strings are processed. In FIG. 11, first, NUM = 0 is set (step E1). Next, it is checked whether or not the combination (that is, AB) of the character strings stored in buf1 and buf2 (first and second in the work buffer) is registered in the dictionary (step E2). When it is determined that the character string is registered, the combination of the character strings stored in buf1 and buf2 is replaced with the registration number of the dictionary, and the next character string (that is, B) is added to the buf16 in which a space is created by this replacement. Store (step E3). Then, the process returns to step E2, and it is checked again whether or not the combination of the character strings buf1 and buf2 is registered in the dictionary.

On the other hand, in step E2, buf1, buf
When it is determined that the combination of the character strings of 2 is not registered in the dictionary, it is checked whether or not the combination of the character strings of buf2 and buf3 is registered in the dictionary (step E4). If it is registered, the process proceeds to step E5 and then returns to step E2. If not registered, move to the next step.

Thus, the combination of the character strings buf15 and buf16 is checked (step E8),
If this combination of character strings is not registered, it is checked by the final path flag whether the current path is the final path (step E10). If it is not the final pass, the process proceeds to step E11, where buf1 and buf are set.
A combination of two character strings is newly registered in the dictionary. Then, the character string stored in buf1 is erased, the character string in the work buffer is shifted to the left, and the next character string is stored in buf16 so as to fill the space created thereby. Further, NUM = NUM + 1 is set, the value of NUM is incremented by 1, and then the process returns to step E2. On the other hand, if the final pass is determined in step E10, buf
The character string of 1 is output to the outside as compressed data, and buf1
Erase the character string of and shift to the left by one character, and empty buf16
The next character string will be put in (step E12).

In FIG. 11, for example, step E8,
After E9, the process returns to step E2, but it is not always necessary to return to step E2 in the present invention. That is, in this case, the replacement character strings are buf15 and buf16.
Since it is only the character string stored in, it suffices to return to step E6, which affects the determination. This also applies to other steps such as step E6.

When the above processing is repeated and all the character strings to be compressed are stored in the work buffer and the first pass ends, NUM2 = NUM is set as shown in FIG. 12 (step F2). Here, NUM is the step E1 in FIG.
It is incremented by 1 each time it passes 1, and corresponds to the number of times the compressed data is output (actually, step E1
As indicated by 1 and E12, the compressed data is not output until the final pass).

Next, as shown in step F3, the second pass is performed. In this second pass, the dictionary updated in the first pass is used, and the dictionary is matured. This second pass is performed for all the compression target character strings by the processing shown in FIG. 11, similarly to the first pass. Next, in step F4, NUM> NUM2
It is determined whether or not. When NUM ≦ NUM2, it means that the compressed data output count NUM in step F3 is smaller than the compressed data output count NUM2 in step F1, which means that the data compression rate is improved. Therefore, in this case, the procedure returns to step F2,
The process is repeated until the optimal dictionary is obtained. When NUM> NUM2, it is determined that the optimum dictionary is generated, the final path flag is set to 1 (step F5), and the final path compression operation is performed (step F6).

In the final pass compression operation, since the final pass flag = 1, the determination at step E10 in FIG. 11 is always in the direction of YES, and the process always goes to step E12. That is, in this case, step E12
The character string stored in buf1 is output to the outside as compressed data each time the data passes through. In step E12, a new character string is not registered in the dictionary as in step E11, and the dictionary remains the dictionary used in the previous pass and is not updated. Then, the dictionary that is not updated is output as a static dictionary together with the compressed data to the outside and stored in the storage device or the like.

(D) Frequency of Use Now, in the process of creating an optimal dictionary as described above, the number of registered dictionary reaches the limit, and an attempt is made to newly register a frequently used character string in the dictionary. There may be cases where you cannot register. In this case, the registered character string that is rarely used is erased, and the character string to be registered is written in the empty portion created by the erasure.

FIG. 13A shows the structure of a dictionary containing such usage frequency information, and FIG. 13B shows a flowchart of registration deletion processing based on this usage frequency.

Here, P represents the registration number of the dictionary to be newly registered, and the initial value of P is 256. Then, as shown in FIG. 13A, registration numbers of 256 to 4095 are assigned to the registration locations of the dictionary.
The location of each registration number includes a location for entering the first letter number, a location for entering the second letter number, and a location for entering the frequency of use. The initial value of the usage frequency is all "0",
Usage frequency = 0 indicates that no registered character string is registered at that location.

To newly register a character string consisting of a combination of the first character and the second character, as shown in step G1 of FIG. 13B, the location of P in the dictionary (see FIG. 13).
The character string of the first character and the second character is written in the (258th place in (A)). Next, P = P + 1 is set (step G
2) Look at the next place (place number 259). in this case,
When P = 4096, P = 256 is set (steps G3 and G4). Next, the usage frequency of the location of P (location 259) is checked (step G5), and if the usage frequency> 1, the usage frequency of the location of P is decremented by 1 (step G7). Then, the process returns to step G2 again, and P = P +
Look at the next place (No. 260) as 1.

For example, consider a case where there are no empty spaces in the locations 256 to 4095 in the dictionary. In this case, steps G2 to G are repeated until there is a place where the frequency of use = 0.
The process of 5 is repeated. And first, the frequency of use = 0
The registration of the place that has become is deleted (step G6). Then, when newly registering a dictionary, the dictionary is registered in this deleted location.

By the above processing, the registration numbers 256-40
In 95, it is possible to delete the registered character string that is least frequently used, and it is possible to newly register another character string at the place where this registration is deleted. As a result, it becomes possible to generate a dictionary in which registered character strings that are frequently used are preferentially registered.

(E) Restoration Processing The dictionary created by this embodiment has a tree structure as follows. (Dictionary) 256: 30 + 56 257: 80 + 16 258: 256 + 257 259: 256 + 257 260: 259 + 257 Therefore, according to this dictionary, for example, registration numbers 256-260.
When the registered character string registered in is restored, it becomes as follows. (Character string restoration) 256 = 30 + 56 257 = 80 + 16 258 = 256 + 40 = 30 + 56 + 40 (from 256 = 30 + 56) 259 = 256 + 257 = 30 + 56 + 257 (from 256 = 30 + 56) = 30 + 26 + 80 + 16 (from 257 = 80 + 16) 260 = 259 + 257 + 257 (257) = 256 + 257 + 257 (from 256 = 30 + 56) = 30 + 56 + 257 + 257 (from 257 = 80 + 16 = 30 + 56 + 80 + 16 + 257 = 30 + 56 + 80 + 16 + 80 + 16 (from 257 = 80 + 16) In this way, the registered character string is reconstructed in order to restore the compressed character string. It is necessary to perform decomposition processing until all character strings are smaller than 256. However,
If the above decomposition processing is performed when restoring, there is a problem that the restoring speed of the character string becomes very slow. Therefore, in order to solve this problem, a restoration-specific dictionary as described below is generated from the generated dictionary, and this restoration-specific dictionary is stored in a storage medium such as a ROM and used for restoration. Is desirable.

FIG. 14A shows the structure of this restoration-only dictionary. A character string length (data length) and information on the character string start address are stored in the head portion of the restoration-only dictionary side by side in the order of registration numbers 256 to 4095.
And after that, the core part of the string (list of strings)
Is stored. As described above, the core part of this character string is generated by performing decomposition processing until all the character strings forming the registered character string are smaller than 256. These character strings are registered for restoration only. It becomes a character string.

When performing the restoration process, as shown in FIG. 14B, the corresponding start address in the core portion of the character string is determined by the character string start address stored at the positions of registration numbers 256 to 4095. Is specified. Then, the data is restored by extracting a character string (restoration-dedicated registration character string) of a length designated by the character string length from the start address. In this case, since the core part of the character string has been decomposed in advance as described above, the speed of the restoration process can be made much faster than that of the tree structure dictionary.

FIG. 15 shows a flowchart of the restoration process when the dictionary dedicated to the restoration is used. First,
In step H2, the 12-bit code is read, and if the code is an end symbol, the processing ends (step H2).
4) If it is not the end symbol, the process proceeds to step H5. Then, information on the character string start address and the character string length to be restored from the dictionary is obtained according to the code number. Then, the character string of the character string length is written from the obtained character string start address in the restoration buffer (step H6). Data can be restored by repeating the above processing until the end symbol is detected.

3. Third Example The third example is an example in which so-called font data is compressed by the data compression method described in the first and second examples above.

(A) Bitmap Font Data First, the case of compressing bitmap font data will be described. Bitmap font data is usually arranged in the raster direction. However, when compressing bitmap font data according to the present embodiment, the compression ratio is considerably better when compressed in the vertical direction. Therefore, FIG.
As shown in (A), data is compressed in the vertical direction. However, of course, data compression may be performed in the horizontal direction.

As shown in FIG. 16A, the bitmap font data (40 dots × 40 dots) is formed by arranging five data blocks each having a fixed length of 40 bytes. In this embodiment, the first and second data blocks are set for each data block.
The compression is performed by the compression method shown in the embodiment. Normally, data compression is performed in this manner. However, when the restoration speed is prioritized over the compression rate, the data is not displayed in byte string units as shown in FIG. 16A, but as shown in FIG. 16B. 2 side by side
It is also possible to perform data compression in units of word strings with one byte as one word. This makes it possible to increase the restoration speed, but on the other hand, there is a problem that the number of character strings that can be registered in the dictionary needs to be about 32768.

In FIG. 17, for example, the character "ni"
The one shown in the bitmap image is shown. FIG. 17
In, the part where "1" is written becomes black. Then, "0" is written in the other part, and this part becomes white. As is clear from FIG. 17, 0-7, 1
The byte string (data string) of Nos. 2, 13, 30 to 39 is 00
h (hexadecimal display). Also, 10, 11, 14-1
The byte string of Nos. 6, 27 to 29 is 01h. Also, 8
No. byte sequence is 02h, and No. 9, 17-26 byte sequences are 03h. In this way, when the bitmap font data is compressed in the vertical direction, the byte strings of the same value continue. Therefore, it is understood that the data compression methods of the first and second embodiments compress the data with high efficiency.

(B) Outline Font Data The outline font is intended to represent the outline of a character by a number of points and a straight line or a curve connecting them. For normal size characters (for example, 10 points), print using the above bitmap font.
Some users may want to print in a large size such as 32 points. In such a case, it is difficult to prepare the bitmap font data of each size in advance due to the data capacity. Therefore, in such a case, a basic outline font is held for each character, the outline of the character is represented by this outline font, and the outline is enlarged by scaling, and this is expanded into a bitmap as shown in FIG. Convert to image data. This makes it possible to print characters of a desired size.

For example, as shown in FIG. 18, the outline of the character "2" by the outline font is formed by the points A, B, C, D, E, F, G ... Can be represented. In this embodiment, the outline font data is described in a data format called NSI format.

In the present embodiment, the outline font data described in this NSI format is represented in FIG.
As shown in FIG. 9 (A), there are three parts, that is, FLG part, D
The AT part and the VCT part are separated and compressed.

Here, the VCT portion is information representing vector coordinates in the launch direction at each point, and X, Y at each point.
Contains vector coordinate information. It should be noted that these X and Y vector coordinates do not represent absolute values of the coordinates but represent relative values from the immediately preceding point.

The FLG portion is information representing the attribute of each point. For example, "A point is a starting point", "A point and B point".
"Points are connected by a straight line", "B points and D points are connected by a curve (Bezé curve) with C point as an intermediate point", "D points and E points are connected by a straight line", "E points and G" The points are connected by a curve (Beeze curve) having the F point as an intermediate point. " Further, the DAT portion is information indicating the characteristics of the character, and includes information indicating the size of the character, information indicating the line width of the character, and the like. In this embodiment, the VCT part is compressed by the Huffman coding method. On the other hand, since the FLG portion and the DAT portion have some degree of regularity such as the same data continues, they are compressed by the data compression method described in the first and second embodiments.
By separating and compressing the components forming the outline font data for each component in this way, the compression rate can be significantly improved. The structure of the data after compression is, as shown in FIG. 19 (B), first only the compressed data of the FLG part is arranged, then only the compressed data of the DAT part is arranged, and then the compressed data of the VCT part. The structure is such that only chimneys line up. Also, the FLG part, DAT
A dedicated restoration dictionary corresponding to each of the parts and the VCT parts is prepared.

When restoring this compressed data, the FLG
Part, DAT part, and then V
The CT portion will be restored. FIG. 19C shows a flowchart of this restoration processing. First, in step I2, the FLG portion is restored with the FLG static dictionary, and this is temporarily written in the buffer provided for the FLG. Next, in step I3, the DAT portion is restored with the static dictionary for DAT, and this is temporarily written in the buffer provided for DAT. In this state, the pointer for reading data is V compressed as shown in FIG.
It will point to the beginning of the CT portion.

Next, as shown in step I4, DAT
After reading the portion and the FLG portion from the buffer according to the rules of the NSI format and outputting them, the VCT portion is Huffman coded according to bits 0 to 3 of the read FLG portion (details of these bits will be described later). Restore to. This makes it possible to obtain the original outline font data returned in the NSI format order.

In the present embodiment, in order to further improve the data compression rate, the FLG part and the VCT part are changed to a format that can be expressed by the coordinate point control unit and coordinate point definition unit described below, and then compressed. It is carried out.

Here, the bits 4 to 7 of the coordinate point control unit are the same as the bits 4 to 7 of the original FLG portion. These bits 4 to 7 specify the attribute of each point,
That is, it is designated which of a start point, an intermediate point, an end point, movement interpolation, linear interpolation, and curve interpolation. Bit 0 to bit 3 of the coordinate point control unit indicate that the value of the vector coordinate defined in the coordinate point definition unit has the following meaning. That is, bit 0 represents that the X vector coordinate is a non-zero value and exists, and bit 1 represents that the Y vector coordinate is a non-zero value and exists. Bit 2 indicates that the X vector coordinate is a negative value. Further, bit 3 represents that the Y vector coordinate has a negative value.

A 10-bit code (0
1023) are lined up. Then, by specifying these codes and bits 0 to 3 of the coordinate point control unit, it is possible to represent a vector coordinate value in the range of −1024 ≦ X vector coordinate ≦ 1024 −1024 ≦ Y vector coordinate ≦ 1024.

For example, when bit 0 = 1, it is indicated that there is X-1 data in the coordinate point definition section. Further, when bit 1 = 1, it is indicated that the coordinate point defining portion has Y-1 data. When a character has a vertical bar, a horizontal bar, or the like, the X vector coordinate may be 0 or the Y vector coordinate may be 0.
It is not necessary to output vector coordinates and Y vector coordinates as compressed data. Therefore, in this case, if the presence or absence of the X vector coordinate and the Y vector coordinate in the coordinate point definition unit can be specified by controlling bits 0 and 1 of the coordinate point control unit, the data compression rate can be further improved. Become. Further, the positive / negative designation of the X vector coordinate and the Y vector coordinate is designated by the bits 2 and 3 of the coordinate point control unit as described above, whereby the data compression rate can be further improved.

As described above, according to this embodiment, bitmap font data and outline font data can be effectively compressed. Then, at the time of this compression, the static dictionary described in the first and second embodiments is used. In this case, it is desirable that the static dictionary is a common static dictionary for characters of a common font (font). For example, for the characters in Mincho type, all the dictionaries dedicated to Mincho type are used to update the dictionary and compress the data to obtain the final static dictionary and compressed data. In addition, for Gothic characters, the dictionary is updated and data is compressed using the Gothic-specific dictionary, and the final static dictionary,
Get compressed data. By using a common dictionary for each font in this way, data can be efficiently compressed. This is because if the fonts are common, for example, the method of changing the outline of the character (how the line jumps up, etc.) and the thickness of the outline are common to each character, so the characteristic information of the character itself, each outline This is because the point attribute information and the like are the same and the data is easily compressed by this common dictionary. In this case, the output static dictionary and compressed data are classified into each font and stored in the storage device.

FIG. 20 shows how the data compression method of this embodiment described above is used. The compression target data string (font data) is input to the data compression device 31,
Data is compressed by the data compression method of this embodiment. Then, the static dictionary and the compressed data thus generated are stored in the storage device (ROM or the like) in the data decompression unit 32. The data restoration means 32 is built in the information processing apparatus, for example, the printer 33, the computer 34, or the like (the restoration means may be divided and built in two devices).

In a conventional printer or the like, font data or the like is stored in a storage device without being compressed, and the storage address of each compressed data is managed to output the necessary font data at any time to print characters. Was there.
On the other hand, according to the present embodiment, the static dictionary and the compressed data are stored in the storage device, and the storage address of each compressed data and the static character string dictionary are managed to output the necessary character at any time. Is possible. As a result, the amount of data stored in the storage device can be reduced, and the cost of the device can be reduced. Such an advantage is particularly effective for Kanji characters, Hangul characters, etc., which require a large storage capacity, but of course it is also effective for characters of other languages.

The present invention is not limited to the above embodiments, and various modifications can be made within the scope of the gist of the present invention.

For example, although the present embodiment has mainly described processing of character string data, it can be applied to other symbol data and the like.

The data string compressed according to the present invention is not limited to a character string, a byte string, and a word string, and various data strings are included. For example, a data string for forming a two-dimensional or three-dimensional figure, etc. Can also be included.

Further, the registration number in the present invention also includes information having substantially the same function as this registration number.

[0151]

According to the first aspect of the present invention, since the optimum dictionary is used as a static dictionary and data compression is performed by this static dictionary, the data amount of the output static dictionary and the compressed data is optimized. It can be anything. As a result, the capacities of the static dictionary, the storage device storing the compressed data, and the storage medium can be reduced, and the cost can be reduced. Further, for example, it becomes possible to use a data compression algorithm using a dynamic dictionary having a high data compression rate, and the data compression rate can be greatly increased. It is also possible to freely restore the required data string using this static dictionary. For example, when restoring this compressed data string by an information processing device or the like, the desired data string can be arbitrarily retrieved. Is possible. Further, according to the present invention, there is a possibility that it takes a long time to optimize the dictionary and obtain a final dictionary and compressed data, but there is also an effect that the decompression processing speed itself does not become particularly slow.

According to the second aspect of the invention, the combination of the data strings having a large number of combinations is preferentially replaced by the registration number of the dictionary, so that the data compression rate can be optimized. it can. On the other hand, the registration of the registration data string that is used infrequently is deleted, and the update ends when the number of registrations reaches a predetermined number. Therefore, it is possible to generate an optimal dictionary with a small amount of data. There is also an advantage that a dictionary can be easily generated by a method called a slide dictionary. Note that the predetermined number in this case can be set such that when the number of bits of the output data is 12 bits, for example, the number of registered dictionaries falls within the range of 12 bits.

Further, according to the third aspect of the invention, the combination of the data strings having a high appearance probability is preferentially replaced by the registration number, so that the data compression rate can be optimized. On the other hand, the registration of the registration data string that is used infrequently is deleted, and the update ends when the number of registrations reaches a predetermined number. Therefore, it is possible to generate an optimal dictionary with a small amount of data. Since the first dictionary can be generated by one analysis, there is also an advantage that the processing can be greatly simplified.

Further, according to the invention of claim 4, the data compression is performed by the data compression algorithm using the dynamic dictionary having a high data compression rate, and the dictionary update is completed at the stage where the data compression rate is optimum. The data compression rate can be greatly increased. On the other hand, since the output dictionary becomes a static dictionary, it is possible to freely restore a necessary data string using this static dictionary.

Further, according to the invention of claim 5, especially when compressing the same data string, the number of registered dictionary can be made very small as compared with the conventional incremental decomposition method, and the dictionary can be reduced. The compressed data itself, which has been replaced with the registration number and compressed, can have a very small data amount as compared with the conventional incremental decomposition method.

According to the sixth aspect of the present invention, the data compression rate can be greatly increased, and a necessary data string can be freely restored using this static dictionary.
There is also an advantage that it is possible to judge whether or not the optimum compression ratio is obtained only by the number of times the process is repeated.

Further, according to the invention of claim 7, when there is a limit to the number of dictionaries that can be registered, the data amount of the dictionaries can be made the optimum size by a very simple method.

Further, according to the invention of claim 8, the data amount of the dictionary can be set to the optimum size, and the registered data string which is frequently used can be left in the dictionary, and the optimum dictionary can be generated. .

According to the invention of claim 9, the bitmap font data and the outline font data can be compressed, and the capacity of the storage device and the storage medium for storing these font data can be reduced.
This makes it possible to reduce the cost of the storage device, the printer including the storage medium, the computer, and the like.

According to the tenth aspect of the invention, the compression method to be applied can be changed according to the characteristics of the data, and the data compression rate can be further increased.

According to the eleventh aspect of the present invention, it is possible to use a common dictionary for each font such as Mincho and Gothic. For example, the method of changing the outline of a character, the thickness of the outline, etc. are often common for the same font,
According to the present invention, it becomes possible to compress data more efficiently.

According to the twelfth aspect of the invention, it is possible to save the capacity and the like required for storing characters.

According to the thirteenth aspect of the present invention, the restoration-dedicated registration data string is converted into the restoration-dedicated data format. For example, in the incremental decomposition method or the additive decomposition method, the registration data string is deleted until the tree structure disappears. Has been disassembled. Therefore, the restoration process can be performed much faster than when using a normal dictionary.

According to the fourteenth aspect of the present invention, it is possible to perform a predetermined process, for example, a process such as character printing, by using the restored data string.

According to the fifteenth aspect of the invention, the original data string can be restored by the restoring means, and this restoring means can be incorporated in an information processing device such as a computer or a printer.

[Brief description of drawings]

FIG. 1 is a flowchart illustrating a data compression method according to a first embodiment.

FIG. 2 is a block diagram showing an example of a configuration of a data compression device 12 in which the data compression method of the embodiment is used.

FIGS. 3A to 3E are schematic explanatory diagrams for explaining a method of a slide dictionary.

FIG. 4 is a flow chart for explaining a method of obtaining an optimum dictionary using a slide dictionary method.

FIG. 5 is a flowchart for explaining a method of obtaining an optimum dictionary by using the incremental decomposition algorithm.

FIG. 6 is a diagram visually showing a process of creating a static dictionary and compressed data.

FIG. 7 is a schematic explanatory diagram for schematically explaining the data compression method used in the second embodiment.

8A and 8B are diagrams schematically showing the difference in processing between the incremental decomposition method and the additive decomposition method.

FIG. 9 is a flowchart for explaining the operation of the incremental decomposition method.

10A and 10B are diagrams schematically showing the difference in processing between the incremental decomposition method and the additive decomposition method.

FIG. 11 is a flowchart for explaining processing of one pass by the additive incremental decomposition method.

FIG. 12 is a flowchart for explaining processing of a plurality of passes for dictionary optimization.

13A is a diagram showing a structure of a dictionary including usage frequency information, and FIG. 13B is a flowchart showing a registration deletion process based on usage frequency.

FIG. 14 (A) is a diagram showing a structure of a restoration-only dictionary, and FIG. 14 (B) is a diagram explaining designation of a core portion of a character string by a character start address and a character string length. .

FIG. 15 is a flowchart of restoration processing when a dictionary dedicated to restoration is used.

16A and 16B are schematic explanatory diagrams for explaining compression of bitmap data.

FIG. 17 is a schematic explanatory diagram for explaining a bitmap image of a character.

FIG. 18 is a schematic explanatory diagram for explaining an outline font.

19A and 19B are schematic explanatory diagrams for explaining the compression of outline font data, and FIG. 19C is a flowchart of the decompression process of this compressed data.

FIG. 20 is a mode of using the data compression method according to the embodiment.

[Explanation of symbols]

 1 Character string data to be compressed 2 Working buffer 3 Dictionary 4 Compressed data 5 Completed dictionary 11 All data strings to be compressed 12 Data compression device 13 Dictionary generating means 14 Static dictionary 15 Static dictionary holding means 16 Static Dictionary output means 17 data compression means 18 compressed data output means 19 compressed data

Claims (15)

[Claims] 1. A data compression method for performing data compression by using a dictionary capable of registering a registration data string in association with a registration number and replacing two or more combinations of data strings with the registration number, which is a compression target. The dictionary is updated until the optimum dictionary for data compression of the data string is generated, and when the optimum dictionary is generated, the dictionary is output as the final static dictionary for decompression, and the static dictionary A data compression method, which comprises compressing a data string to be compressed and outputting the compressed data string as final compressed data for decompression. 2. The update of the dictionary according to claim 1, wherein the update of the dictionary until the optimum dictionary is generated,
A feature is that registration of a registration data string that is used less frequently is deleted from a dictionary generated by preferentially registering a combination of data strings with a large number of combinations until the number of registrations in the dictionary reaches a predetermined number. Data compression method. 3. The update of the dictionary according to claim 1, wherein the update of the dictionary until the optimum dictionary is generated,
A feature is that registration of a registration data string that is used infrequently is deleted from a dictionary generated by preferentially registering a combination of data strings with a high appearance probability until the number of registrations in the dictionary reaches a predetermined number. Data compression method. 4. The update of the dictionary according to claim 1, wherein the update of the dictionary until the optimum dictionary is generated,
The dictionary is dynamically changed during data compression. While the dictionary is being updated by the data compression algorithm, the data compression process is performed on all the data strings to be compressed, and the data updated again by using the dictionary updated by the process. A data compression method characterized by performing data compression processing on all data strings to be compressed while updating a dictionary by a compression algorithm, and repeating the processing until the data compression rate becomes optimum. 5. A data compression method for compressing data by using a dictionary capable of registering a registration data string in association with a registration number and replacing two or more combinations of the data strings with the registration number, which comprises (A) compression. A combination of a step of extracting a predetermined number of data strings from a target data string and storing them in a work area having a predetermined number of buffers and (B) a combination of data strings stored in adjacent buffers in the work area is registered in a dictionary. If it is registered in the dictionary, the combination of the data string is replaced with the registration number in the dictionary, and the data string is set in the work area so as to fill the empty buffer created by the replacement. After shifting, the subsequent data string is fetched into the empty buffer created at the end of the work area, and it is saved again in the adjacent buffer in the work area. Either of the step of analyzing whether the combination of the data strings to be stored is registered in the dictionary or (C) the combination of the data strings stored in the adjacent buffers in the work area by the analysis of the step (B). If it is determined that Momo is not registered in the dictionary, the combination of the data strings stored in the first and second buffers in the work area is registered in the dictionary and the first data string is deleted. Then, the data string is shifted in the work area so as to fill the empty buffer created by the erasure, and the subsequent data string is loaded into the empty buffer created at the end of the work area, which is the object of compression. A data compression method characterized in that the steps (B) and (C) are repeated until all the data strings are stored in the work area. 6. The method according to claim 5, wherein when the processes (B) and (C) are repeated until all the data strings to be compressed are processed in one pass, A data compression method for compressing data in the current pass using the dictionary updated in the pass, wherein the number of repetitions of the steps (B) and (C) in the current pass is equal to or less than the number of repetitions in the previous pass. If the number of repetitions of the steps (B) and (C) in the current pass is larger than the number of repetitions in the previous pass, the dictionary updated in the previous pass is finally determined. Data as a static dictionary for decompression, data compression of one pass by the static dictionary, and outputting a compressed data string as final compressed data for decompression. Compression method. 7. The method according to claim 1, wherein the dictionary stores a registration number and a registration data string together with usage frequency information, and includes a step of sequentially deleting a registration data string having a low usage frequency. Data compression method. 8. The deletion of a registration data string having a low frequency of use according to claim 7, wherein the number of times of use of the registration data string registered in the dictionary is gradually reduced, and the number of times of use is first below a predetermined number. The data compression method is performed by preferentially deleting the registered data sequence that has been deleted. 9. The data compression method according to claim 1, wherein the data string to be compressed is font data necessary for printing characters. 10. The character string according to claim 9, wherein only a part of the font data is a data string to be compressed, and the other part is data-compressed by another data compression method. Data compression method. 11. The data compression method according to claim 9, wherein the characters having a common font are subjected to data compression using the common dictionary. 12. The data compression method according to claim 1, wherein the data string to be compressed is a character string. 13. The restoration according to claim 1, wherein the registration data string is converted into a data format dedicated to the restoration from the registration number and the information of the registration data string included in the finally generated dictionary. A data compression method, wherein a decompression-only dictionary is generated that includes a dedicated registration data sequence, a data length of the decompression-only registration data sequence, and information of a start address of the decompression-only registration data sequence. 14. A data string compressed by a decompression process according to the data compression method, using the compressed data generated by the data compression method according to claim 1 and a final dictionary. A method for restoring data, which is characterized by restoring. 15. A data string which is a compression target by a decompression process according to the data compression method, using the compressed data generated by the data compression method according to claim 1 and a final dictionary. An information processing apparatus comprising means for restoring the information.