WO2016155627A1

WO2016155627A1 - Method and apparatus for recognizing characters in picture

Info

Publication number: WO2016155627A1
Application number: PCT/CN2016/077865
Authority: WO
Inventors: 薛永刚; 贾文杰; 项碧波
Original assignee: 北京奇虎科技有限公司; 奇智软件（北京）有限公司
Priority date: 2015-04-03
Filing date: 2016-03-30
Publication date: 2016-10-06
Also published as: CN104766077B; CN104766077A

Abstract

A method and apparatus for recognizing characters in a picture. The method comprises: recognizing character placeholders contained in a picture, and acquiring a candidate character set corresponding to each character placeholder and a probability parameter corresponding to each candidate character (S110); sequentially selecting a candidate character from the candidate character set corresponding to each character placeholder to obtain a candidate character combination according to the sequence of the character placeholders contained in the picture; performing selection many times, selecting different character combinations each time, and obtaining a plurality of candidate character combinations (S120); calculating the probability of each obtained candidate character combination (S130), and using a candidate character combination having the highest probability as a character recognition result of the picture (S140). By means of the technical scheme, image information is completely and accurately converted into text information capable of being recognized and processed by a computer, character information in the picture is automatically extracted and does not need to be input manually by a user, and user needs are met.

Description

Method and device for recognizing characters in pictures

Technical field

The present invention relates to the field of computer technologies, and in particular, to a method and apparatus for recognizing characters in a picture.

Background technique

Nowadays, with the increasing popularity of information technology and terminal technology, how to input characters into the terminal conveniently and quickly has become an important problem affecting the efficiency of human-machine interface. In the prior art, most users still rely on traditional keyboard input or handwriting input to complete character input, which can meet the basic input requirements of the user. However, the traditional input method also brings a lot of inconvenience to the user. For example, when the user has a question about the characters contained in an image and needs to search, the characters contained in the image need to be manually input into the search bar. Or, when the user needs to save the phone number in an image, the phone number contained in the picture needs to be recorded elsewhere, and then manually entered into the phone book. It can be seen that because the terminal cannot recognize the characters contained in the picture, the user's processing of the characters contained in the picture is time consuming and laborious, and does not meet the needs of the user.

Summary of the invention

In view of the above problems, the present invention has been made in order to provide a method and apparatus for recognizing characters in a picture that overcomes the above problems or at least partially solves or alleviates the above problems.

According to an aspect of the present invention, a method of identifying a character in a picture is provided, the method comprising:

Identifying a character placeholder included in the picture, obtaining a candidate character set corresponding to each character placeholder and a probability parameter corresponding to each candidate character;

According to the order of the characters occupied by the picture, one candidate character is selected from each candidate character set corresponding to each character placeholder to obtain a candidate character combination; multiple selections are performed, and different character combinations are selected each time. , obtaining multiple candidate character combinations;

Calculate the probability of each candidate combination of characters obtained,

The candidate characters with the highest probability are combined as the result of character recognition for the picture.

According to still another aspect of the present invention, an apparatus for recognizing characters in a picture is provided Set includes:

An obtaining unit, configured to identify a character placeholder included in the picture, obtain a candidate character set corresponding to each character placeholder, and a probability parameter corresponding to each candidate character;

The pre-processing unit is adapted to select one candidate character from the candidate character set corresponding to each character placeholder in turn according to the order of the characters occupied by the picture to obtain a candidate character combination; Select different character combinations to get multiple candidate character combinations;

The identifying unit is adapted to calculate the probability of each of the obtained candidate character combinations, and combine the candidate characters with the highest probability as the character recognition result for the picture.

According to still another aspect of the present invention, a computer program comprising computer readable code, when the computer readable code is run on a terminal device, causes the terminal device to perform the identification picture of any of the above The method of characters in .

According to still another aspect of the present invention, a computer readable medium storing a computer program as described above is provided.

It can be seen from the above that the probability of the candidate character set corresponding to the character placeholder included in the picture and the probability parameter corresponding to each candidate character is calculated, and the probability of all candidate character combinations that may be included in the picture is calculated, and the probability is the highest. The candidate character combination is used as a technical solution for the character recognition result of the picture, and the image information is converted into text information that can be recognized and processed by the computer, which greatly improves the efficiency of the user in storing, retrieving and processing the character information in the picture.

The above description is only an overview of the technical solutions of the present invention, and the above-described and other objects, features and advantages of the present invention can be more clearly understood. Specific embodiments of the invention are set forth below.

DRAWINGS

Various other advantages and benefits will become apparent to those skilled in the art from a The drawings are only for the purpose of illustrating the preferred embodiments and are not to be construed as limiting. Throughout the drawings, the same reference numerals are used to refer to the same parts. In the drawing:

1 shows a flow chart of a method of identifying characters in a picture, in accordance with one embodiment of the present invention;

2 illustrates a method of identifying search keywords in accordance with one embodiment of the present invention. Flow chart

3 shows a schematic diagram of an apparatus for identifying characters in a picture, in accordance with one embodiment of the present invention;

4 shows a schematic diagram of an apparatus for identifying search keywords in accordance with one embodiment of the present invention;

FIG. 5A shows a schematic diagram of a picture for character recognition according to an embodiment of the present invention; FIG.

FIG. 5B shows a schematic diagram of a first picture according to another embodiment of the present invention; FIG.

FIG. 5C is a schematic diagram showing a second picture according to another embodiment of the present invention; FIG.

Figure 6 shows schematically a block diagram of a terminal device for carrying out the method according to the invention;

Fig. 7 schematically shows a storage unit for holding or carrying program code implementing the method according to the invention.

Specific embodiment

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While the embodiments of the present invention have been shown in the drawings, the embodiments Rather, these embodiments are provided so that this disclosure will be more fully understood and the scope of the disclosure will be fully disclosed.

1 shows a flow chart of a method of identifying characters in a picture, in accordance with one embodiment of the present invention. As shown in Figure 1, the method includes:

Step S110, identifying a character placeholder included in the picture, acquiring a candidate character set corresponding to each character placeholder and a probability parameter corresponding to each candidate character.

Step S120: sequentially select one candidate character from the candidate character set corresponding to each character placeholder according to the order of each character occupying position of the picture to obtain a candidate character combination; perform multiple selections, and select different characters each time. Combine to get multiple candidate character combinations.

Step S130, calculating the probability of each of the obtained candidate character combinations.

In step S140, the candidate characters with the highest probability are combined as the character recognition result for the picture.

It can be seen that the method shown in FIG. 1 obtains all candidate characters that may be included in the image by acquiring a candidate character set corresponding to the character placeholder included in the picture and a probability parameter corresponding to each candidate character. The combined probability is calculated, and the candidate character with the highest probability is combined as the character recognition result for the picture. The program can convert the image information into text information that can be recognized and processed by the computer, which greatly improves the efficiency of the user in storing, retrieving and processing the character information in the picture.

In an embodiment of the present invention, step S110 of the method shown in FIG. 1 uses an optical character recognition (OCR) technology to identify a character occupying position included in a picture, and obtains a candidate character set corresponding to each character placeholder and The probability parameter corresponding to each candidate character.

In one embodiment of the present invention, the probability of each of the candidate character combinations obtained by step S130 of the method shown in FIG. 1 is: based on the n-gram model, the probability of each of the candidate character combinations obtained is calculated. Specifically, for each candidate character in a candidate character combination, a conditional probability that the candidate character appears under the condition that the first n-1 candidate characters have been determined is calculated according to the probability parameter of each candidate character; and the candidate character is calculated. The product of the conditional probabilities of the candidate characters in the combination is taken as the probability of the candidate character combination.

FIG. 5A is a schematic diagram of a picture for performing character recognition according to an embodiment of the present invention. In the specific embodiment shown in FIG. 5A, first, the character occupied by the picture is recognized, and each character place is acquired. The corresponding candidate character set and the result of the probability parameter corresponding to each candidate character are as shown in Table 1:

Table 1

字符占位Character placeholder	每个字符占位对应的候选字符集合a set of candidate characters corresponding to each character placeholder	每个候选字符对应的概率参数Probability parameter corresponding to each candidate character
11	手，季，乎，年，丰Hand, season, care, year, abundance	35，49，51，53，5735,49,51,53,57
22	机，杌，枧，视，枫Machine, 杌, 枧, 视, maple	22，43，52，52，5622,43,52,52,56
33	管，菅，营，營，眚Tube, 菅, camp, camp, 眚	26，49，52，52，5226,49,52,52,52
44	家，冢，象，彖，冻Home, 冢, elephant, 彖, frozen	23，61，81，82，8323,61,81,82,83

As shown in Table 1, there are 4 characters in the picture, and 5 candidate characters are included in the candidate character set corresponding to each character placeholder.

Then, according to the order of the character occupations in the picture shown in FIG. 5A from left to right, one candidate character is selected from each candidate character set corresponding to each character placeholder to obtain a candidate character combination; To a different combination of characters, a combination of 5 ⁴ = 625 candidate characters can be obtained.

In this embodiment, the probability of each candidate character combination is calculated based on the 4-ary grammar model, that is, for each candidate character in a candidate character combination, the probability parameter is calculated according to the probability parameter of each candidate character. The conditional probability that the candidate character appears under the condition that the first three candidate characters have been determined; the product of the conditional probability of each candidate character in the candidate character combination is calculated as the probability of the candidate character combination.

Specifically, taking a candidate character combination "mobile phone housekeeper" as an example, in order to indicate the integrity of the character combination in the picture, the start and end of the character combination should be considered, and the character combination is first processed as "O mobile phone housekeeper $", "O "Expresses the beginning of the character combination, and "$" indicates the end of the character combination. For the "hand" word in "mobile phone housekeeper", the probability of occurrence under the condition that its first three candidate characters have been determined is: P(hand|OOO); for the "machine" word, the first three candidate characters have already The probability of occurrence under certain conditions is: P (machine | OO hand); for the word "pipe", the probability of occurrence under the condition that the first three candidate characters have been determined is: P (tube | O handset); The probability that the word "home" appears under the condition that its first three candidate characters have been determined is: P (home | mobile phone tube); for "$", the probability that it appears under the condition that the first three candidate characters have been determined is :P($|machine housekeeper).

Therefore, the probability of "mobile phone housekeeper" is: P (mobile phone housekeeper) = P (hand | OOO) × P (machine | OO hand) × P (tube | O mobile phone) × P (home | mobile phone tube) × P ($ | Machine Manager). The calculation process of other candidate character combinations is the same, and will not be described again. The candidate character with the highest probability is combined as the character recognition result for the picture. In this embodiment, the candidate character combination with the highest probability is “mobile phone housekeeper”, that is, the character recognition result of the picture shown in FIG. 5A.

2 shows a flow chart of a method of identifying search keywords in accordance with one embodiment of the present invention. As shown in Figure 2, the method includes:

In step S210, in response to the user's touch screen operation, the picture is intercepted according to the operation range to obtain the first picture; and the predetermined area is expanded according to the operation range to perform picture interception, and the second picture is obtained.

Step S220, respectively identifying characters in the first picture and the second picture to obtain corresponding character combinations.

Step S230: Select a character combination from the combination of characters corresponding to the first picture and the second picture as the search keyword after the recognition according to the preset policy.

It can be seen that the method shown in FIG. 2 intercepts two images with different range sizes in response to the user's touch screen operation, and selects two images from each of the two images by separately identifying and then processing the two images according to the preset strategy. The recognition result of the letter is searched as a search keyword. Compared with the prior art, the solution has the following beneficial effects: Firstly, the recognition of the search keyword for the user's touch screen operation is realized, and the user does not need to manually input the search keyword, thereby simplifying the search operation process and meeting the user's needs; secondly, adopting Two ways to comprehensively identify related images, avoiding the missing information in a single picture or More than enough, the accuracy of character recognition in the picture is further improved, thereby improving the accuracy of identifying the search keyword.

In an embodiment of the present invention, step S220 of the method shown in FIG. 2 respectively identifies characters in the first picture and the second picture, and obtains corresponding character combinations as: by identifying the picture as described in any of the above embodiments. The character method respectively identifies the characters in the first picture and the second picture to obtain a corresponding character combination.

In another embodiment of the present invention, step S220 of the method shown in FIG. 2 respectively identifies characters in the first picture and the second picture, and obtaining corresponding character combinations further includes: obtaining pixel coordinates of each character occupying position in the character combination. .

In an embodiment of the present invention, step S230 of the method shown in FIG. 2, according to a preset policy, selecting a character combination from the combination of characters corresponding to the first picture and the second picture as the search keyword includes:

In step S231, in the character combination corresponding to the second picture, the character combination positions corresponding to the first picture are the same and the same length combination is used.

In this step, according to a specific embodiment, specifically, according to the pixel coordinate boundary of the character combination corresponding to the first picture and the second picture, and the pixel coordinates of each character placeholder, the second picture and the first picture are retained. The corresponding character combination position is the same and the length is the same character combination.

Step S232, determining whether the average language model score of the character combination retained in the second picture is smaller than the average model score of the character combination corresponding to the first picture.

In this step, the average language model score of the character combination refers to the logarithm of the probability of the character combination, and the value obtained by averaging the number of characters in the character combination.

Step S233, yes, select a character combination corresponding to the first picture as a search keyword to perform a search; otherwise, select a character combination corresponding to the second picture as a search keyword to perform a search.

5B is a schematic diagram showing a first picture according to another embodiment of the present invention; FIG. 5C is a schematic diagram showing a second picture according to another embodiment of the present invention, and the specific implementation shown in FIG. 5B and FIG. 5C In the example, in response to the touch screen operation of the user, the image is intercepted according to the operation range, and the first picture as shown in FIG. 5B is obtained; and the predetermined area is expanded according to the operation range, and the picture is intercepted, and the second picture as shown in FIG. 5C is obtained. . Identifying the character placeholders included in the first picture, obtaining a candidate character set corresponding to each character placeholder, a probability parameter corresponding to each candidate character, and a pixel coordinate of each character placeholder, and the result is shown in Table 2:

Table 2

The probability of each candidate character combination is calculated based on the 4-ary grammar model, and the character combination with the highest probability of identifying the first picture is “Mobile Phone Easy”. The specific recognition process has been described in detail in the foregoing, and will not be described again.

Similarly, the character occupying position included in the second picture is identified, the candidate character set corresponding to each character placeholder, the probability parameter corresponding to each candidate character, and the pixel coordinate of each character placeholder are obtained, and the result is shown in Table 3. :

table 3

The probability of each candidate character combination is calculated based on the 4-ary grammar model, and the character combination with the highest probability of identifying the second picture is “t’ae. mobile phone housekeeper”. The specific identification process has been described in detail in the foregoing, and will not be described again. According to the pixel coordinates corresponding to each character placeholder, the "t'ae." part of the character combination is located at a higher position in the second picture, and the "phone housekeeper" part is located at a lower position in the second picture.

Then, in the character combination "t'ae. mobile phone housekeeper" corresponding to the second picture, the character combination corresponding to the first picture, "mobile phone tube", has the same character combination and the same length, according to "mobile phone management" and The pixel coordinate boundary of "t'ae. mobile phone housekeeper" and the pixel coordinates of each character placeholder, we can see that in the character combination "t'ae. mobile phone housekeeper" corresponding to the second picture, the "mobile phone housekeeper" part is The phone is easy to use in the same character group with the same length, so keep the "phone butler" character combination in the second picture.

Calculate the logarithm of the probability of "mobile phone housekeeper" and "mobile phone management" separately, and obtain the value obtained by averaging according to the number of characters in the character combination, and get ln[P(Mobile Manager)]/4>ln[P(Mobile Manager) )]/4, therefore, the character combination "mobile phone housekeeper" corresponding to the second picture is selected as the search keyword to be searched.

3 shows a schematic diagram of an apparatus for identifying characters in a picture, in accordance with one embodiment of the present invention. As shown in FIG. 3, the apparatus 300 for recognizing characters in a picture includes:

The obtaining unit 310 is adapted to identify a character placeholder included in the picture, obtain a candidate character set corresponding to each character placeholder, and a probability parameter corresponding to each candidate character.

The pre-processing unit 320 is adapted to select one candidate character from the candidate character set corresponding to each character placeholder in sequence according to the order of the characters occupied by the picture to obtain a candidate character combination; Select different combinations of characters to get multiple candidate character combinations.

The identifying unit 330 is adapted to calculate the obtained probability of each candidate character combination, and combine the candidate characters with the highest probability as the character recognition result for the picture.

It can be seen that the device shown in FIG. 3 acquires the candidate character set corresponding to the character placeholder included in the picture and the probability parameter corresponding to each candidate character through the mutual cooperation of the units, and the probability of all candidate character combinations that may be included in the picture. The calculation is performed to combine the candidate characters with the highest probability as the character recognition result for the picture. The program can convert image information into text information that can be recognized and processed by a computer, which greatly improves the efficiency of data storage, retrieval and processing by users.

In an embodiment of the present invention, the acquiring unit 310 of the apparatus shown in FIG. 3 is adapted to identify a character placeholder included in a picture by using an optical character recognition technology, obtain a candidate character set corresponding to each character placeholder, and each candidate The probability parameter corresponding to the character.

In an embodiment of the present invention, the identification unit 330 of the apparatus shown in FIG. 3 is adapted to be based on n A meta-grammar model that calculates the probability of each candidate combination of characters obtained. Specifically, the identifying unit 330 is adapted to calculate, for each candidate character in a candidate character combination, a condition that the candidate character appears under the condition that the first n-1 candidate characters have been determined according to the probability parameter of each candidate character. Probability; the product of the conditional probability of each candidate character in the candidate character combination is calculated as the probability of the candidate character combination.

The specific implementation is, for example, the embodiment in which FIG. 5A is located, which has been described in detail above, and is not described herein again.

4 shows a schematic diagram of an apparatus for identifying search keywords in accordance with one embodiment of the present invention. As shown in FIG. 4, the apparatus 400 for identifying a search keyword includes:

The image obtaining unit 410 is adapted to perform a picture capture according to the operation range in response to the user's touch screen operation to obtain a first picture; and further expand the predetermined area according to the operation range to perform picture interception to obtain a second picture.

The identification processing unit 420 is adapted to respectively identify the characters in the first picture and the second picture to obtain a corresponding character combination.

The search processing unit 430 is adapted to select a combination of characters from the combination of characters corresponding to the first picture and the second picture as the search keyword after the recognition according to the preset policy.

It can be seen that the device shown in FIG. 4 intercepts two images with different range sizes in response to the user's touch screen operation through the mutual cooperation of the units, and separately processes the two images according to the preset strategy, and then In the picture, select a more reliable recognition result as a search keyword to search. Compared with the prior art, the solution has the following beneficial effects: Firstly, the recognition of the search keyword for the user's touch screen operation is realized, and the user does not need to manually input the search keyword, thereby simplifying the search operation process and meeting the user's needs; secondly, adopting The method of comprehensively identifying two related pictures avoids the lack or surplus of information in a single picture, further improves the accuracy of character recognition in the picture, and further improves the accuracy of identifying the search keyword.

In an embodiment of the present invention, the identification processing unit 420 of the apparatus shown in FIG. 4 is adapted to respectively identify the first picture and the second picture by means of the apparatus 300 for recognizing characters in the picture as described in any of the above embodiments. The characters in the box get the corresponding character combination.

Further, the identification processing unit 420 of the apparatus shown in FIG. 4 is further adapted to obtain pixel coordinates of each character occupying in the character combination.

In an embodiment of the present invention, the search processing unit 430 of the apparatus shown in FIG. 4 is adapted to In the character combination corresponding to the second picture, the character combination position corresponding to the first picture is the same and the length is the same character combination; determining whether the average language model score of the reserved character combination in the second picture is smaller than the character combination corresponding to the first picture The average model score; yes, the character combination corresponding to the first picture is selected as the search keyword for searching; otherwise, the character combination corresponding to the second picture is selected as the search keyword for searching. Specifically, the search processing unit 430 is adapted to retain, according to the pixel coordinate boundary of the character combination corresponding to the first picture and the second picture, and the pixel coordinates of each character placeholder, retain the second picture corresponding to the first picture. A combination of characters with the same position and the same length. Moreover, in one embodiment, the average language model score for the combination of characters refers to the logarithm of the probability of the combination of characters, the value obtained by averaging the number of characters in the combination of characters.

The specific implementations are as shown in the embodiment of FIG. 5B and FIG. 5C, which have been described in detail above, and are not described herein again.

In summary, the technical solution provided by the present invention as a whole, on the one hand, obtains a candidate character set corresponding to a character placeholder included in a picture and a probability parameter corresponding to each candidate character, which may be included in the picture. The probability of all candidate character combinations is calculated, and the candidate character with the highest probability is combined as the character recognition result for the picture. On the other hand, in response to the user's touch screen operation, two pictures with different range sizes are intercepted, and a more reliable recognition result is selected from the two pictures by separately identifying and then processing the two pictures according to the preset strategy. Search as a search keyword. Compared with the prior art, the scheme has the following beneficial effects: 1. Using the natural language n-gram model to correct the recognition problem of the optical character recognition technology itself, and optimizing the effect; 2. Dynamic programming finds the optimal candidate character combination and improves Recognition effect; 3. Comprehensive comparison algorithm of large image and small image, mutual verification and supplement, avoiding the missing or surplus of information in a single picture; 4. Selecting the position and length of the final recognition result based on the pixel coordinates of the small image . The invention improves the accuracy of character recognition in the picture, thereby improving the accuracy of identifying the search keyword, without manual input by the user, improving the search efficiency and meeting the user's demand.

It should be noted:

The algorithms and displays provided herein are not inherently related to any particular computer, virtual device, or other device. Various general purpose devices can also be used with the teaching based on the teachings herein. Root The structure required to construct such a device is apparent from the above description. Moreover, the invention is not directed to any particular programming language. It is to be understood that the invention may be embodied in a variety of programming language, and the description of the specific language has been described above in order to disclose the preferred embodiments of the invention.

In the description provided herein, numerous specific details are set forth. However, it is understood that the embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of the description.

Similarly, the various features of the invention are sometimes grouped together into a single embodiment, in the above description of the exemplary embodiments of the invention, Figure, or a description of it. However, the method disclosed is not to be interpreted as reflecting the intention that the claimed invention requires more features than those recited in the claims. Rather, as the following claims reflect, inventive aspects reside in less than all features of the single embodiments disclosed herein. Therefore, the claims following the specific embodiments are hereby explicitly incorporated into the embodiments, and each of the claims as a separate embodiment of the invention.

Those skilled in the art will appreciate that the modules in the devices of the embodiments can be adaptively changed and placed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and further they may be divided into a plurality of sub-modules or sub-units or sub-components. In addition to such features and/or at least some of the processes or units being mutually exclusive, any combination of the features disclosed in the specification, including the accompanying claims, the abstract and the drawings, and any methods so disclosed, or All processes or units of the device are combined. Each feature disclosed in this specification (including the accompanying claims, the abstract and the drawings) may be replaced by alternative features that provide the same, equivalent or similar purpose.

In addition, those skilled in the art will appreciate that, although some embodiments described herein include certain features that are included in other embodiments and not in other features, combinations of features of different embodiments are intended to be within the scope of the present invention. Within and form different implementations example. For example, in the following claims, any one of the claimed embodiments can be used in any combination.

The various component embodiments of the present invention may be implemented in hardware, or in a software module running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or digital signal processor (DSP) may be used in practice to implement some of some or all of the means for identifying characters in a picture or in accordance with an embodiment of the present invention. All features. The invention can also be implemented as a device or device program (e.g., a computer program and a computer program product) for performing some or all of the methods described herein. Such a program implementing the invention may be stored on a computer readable medium or may be in the form of one or more signals. Such signals may be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

For example, Figure 6 shows a terminal device in which the method according to the invention can be implemented. The and terminal devices conventionally include a processor 610 and a computer program product or computer readable medium in the form of a memory 620. The memory 620 may be an electronic memory such as a flash memory, an EEPROM (Electrically Erasable Programmable Read Only Memory), an EPROM, a hard disk, or a ROM. Memory 620 has a memory space 630 for program code 631 for performing any of the method steps described above. For example, storage space 630 for program code may include various program code 631 for implementing various steps in the above methods, respectively. The program code can be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks. Such a computer program product is typically a portable or fixed storage unit as described with reference to FIG. The storage unit may have a storage section, a storage space, and the like arranged similarly to the storage 620 in the terminal device of FIG. The program code can be compressed, for example, in an appropriate form. Typically, the storage unit comprises computer readable code 631', ie code that can be read by a processor, such as 610, which when executed by the terminal device causes the terminal device to perform each of the methods described above step.

The term "one embodiment", "an embodiment" or "one or more embodiments" is used herein to mean that the specific features, structures, or characteristics described in connection with the embodiments are included. In at least one embodiment of the invention. In addition, it is noted that the phrase "in one embodiment" is not necessarily referring to the same embodiment.

It is to be noted that the above-described embodiments are illustrative of the invention and are not intended to be limiting, and that the invention may be devised without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as a limitation. The word "comprising" does not exclude the presence of the elements or steps that are not recited in the claims. The word "a" or "an" The invention can be implemented by means of hardware comprising several distinct elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means can be embodied by the same hardware item. The use of the words first, second, and third does not indicate any order. These words can be interpreted as names.

In addition, it should be noted that the language used in the specification has been selected for the purpose of readability and teaching, and is not intended to be construed or limited. Therefore, many modifications and changes will be apparent to those skilled in the art without departing from the scope of the invention. The disclosure of the present invention is intended to be illustrative, and not restrictive, and the scope of the invention is defined by the appended claims.

Claims

A method of identifying characters in a picture, wherein the method comprises:

Identifying a character placeholder included in the picture, obtaining a candidate character set corresponding to each character placeholder and a probability parameter corresponding to each candidate character;

According to the order of the characters occupied by the picture, one candidate character is selected from each candidate character set corresponding to each character placeholder to obtain a candidate character combination; multiple selections are performed, and different character combinations are selected each time. , obtaining multiple candidate character combinations;

Calculate the probability of each candidate combination of characters obtained,

The candidate characters with the highest probability are combined as the result of character recognition for the picture.
The method of claim 1 wherein said calculating the probability of each candidate character combination obtained is:

Based on the n-gram model, the probability of each candidate combination of characters obtained is calculated.
The method of claim 1 or 2, wherein the probability of calculating each of the candidate character combinations obtained based on the n-gram model comprises:

For each candidate character in a candidate character combination, calculating a conditional probability that the candidate character appears under the condition that the first n-1 candidate characters have been determined according to the probability parameter of each candidate character;

The product of the conditional probabilities of the candidate characters in the candidate character combination is calculated as the probability of the candidate character combination.
A method according to any one of claims 1 to 3, wherein

The optical character recognition technology is used to identify the character occupying positions included in the picture, and the candidate character set corresponding to each character placeholder and the probability parameter corresponding to each candidate character are obtained.
A device for recognizing characters in a picture, wherein the device comprises:

An obtaining unit, configured to identify a character placeholder included in the picture, obtain a candidate character set corresponding to each character placeholder, and a probability parameter corresponding to each candidate character;

The pre-processing unit is adapted to select one candidate character from the candidate character set corresponding to each character placeholder in turn according to the order of the characters occupied by the picture to obtain a candidate character combination; Select different character combinations to get multiple candidate character combinations;

The identification unit is adapted to calculate the probability of each candidate character combination obtained, and has the highest probability The candidate character combination is used as the character recognition result for the picture.
The apparatus according to claim 5, wherein

The identification unit is adapted to calculate a probability of each of the candidate character combinations obtained based on the n-gram model.
The apparatus according to claim 5 or 6, wherein

The identifying unit is adapted to calculate, for each candidate character in a candidate character combination, a conditional probability that the candidate character appears under the condition that the first n-1 candidate characters have been determined according to the probability parameter of each candidate character; The product of the conditional probabilities of the candidate characters in the candidate character combination is then calculated as the probability of the candidate character combination.
A device according to any of claims 5-7, wherein

The acquiring unit is configured to identify a character occupying position included in the picture by using an optical character recognition technology, obtain a candidate character set corresponding to each character placeholder, and a probability parameter corresponding to each candidate character.
A computer program comprising computer readable code, when said computer readable code is run on a terminal device, causing said terminal device to perform recognition of a character in a picture according to any one of claims 1-4 method.
A computer readable medium storing the computer program of claim 9.