JPH05211614A - Device and method for image processing - Google Patents

Abstract

PURPOSE:To provide the image processor which reproduces an image of high quality when an input image is reproduced by a specific device. CONSTITUTION:The image processor which inputs image data and reproduces the image by the specific device is equipped with a contour extracting circuit 700 which extracts contour vector data along the edge of the input image, a smoothing and coordinate converting circuit 900 which compares the resolution of the input image with the resolution of the reproduction device and smoothes the contour vector data extracted by a contour extracting means according to the comparison result, and a printer 600 which generates a recording image according to the contour vector data smoothed by the smoothing and coordinate converting circuit 900.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing device, and more particularly to an image processing device for inputting image data and outputting it to a predetermined reproducing device.

[0002]

2. Description of the Related Art Conventionally, in an image processing apparatus such as a facsimile machine, an image is read by an image scanner and each pixel of the raster-scanned image is represented by binary data of white or black. Further, when communicating binary raster image data, the binary raster image is encoded and compressed by a method such as MH, MR, MMR, etc., and then transmitted and received. Therefore, in the conventional facsimile apparatus, as the internal representation of the image, the image data is treated as a set of binary raster pixel data, and the image read by G3 fine (main scanning 8 pel / mm, sub scanning 7.7 line / mm) is used. , Standard (main scanning 8 pel / mm, sub scanning 3.8
(5 line / mm) When sending to a receiver that has only a recording resolution of 5 lines / mm and the resolution of the read image on the sending side is different from the resolution on the receiving side, the B4 size received image is output on A4 recording paper. When the paper size of the received image is different from that of the output image, the MH, MR, MMR encoded image data is once converted into binary raster image data, and simply written twice for each pixel (same pixel is written twice or more). (Continued) and thinning processing were used to perform scaling processing such as enlargement and reduction.

[0003]

However, in the above-described conventional example, when recording low-resolution image data on high-resolution data such as recording a 200-dpi image on 400-dpi recording paper, simple pixel-by-pixel Due to the overlap processing, the jagged edges of the diagonal lines are noticeable, and an image with a resolution of G3 fine is scanned in both G4 standard main scanning and sub scanning.
In the resolution conversion in the vicinity of 100% that is converted into an image having a resolution of 00 dpi, there is a problem that the image is distorted because the resolution conversion is performed by the overlapping thinning process for each pixel.

[0004]

SUMMARY OF THE INVENTION The present invention has been made in view of the above prior art, and when reproducing an input image by a predetermined device, an image processing device capable of reproducing a high quality image. Is to provide. In order to solve this problem, for example, the image processing apparatus of the present invention has the following configuration. That is, input image data,
In an image processing device for reproducing an image with a predetermined reproducing device, a contour extracting means for extracting contour vector data along an edge of the input image, and a comparing means for comparing the resolution of the input image with the resolution of the reproducing device. A smoothing means for smoothing the contour vector data extracted by the contour extracting means according to the comparison result of the comparing means; and a recorded image based on the contour vector data smoothed by the smoothing means. And generating means.

Another image processing method of the present invention includes the following steps. That is, in an image processing method of inputting image data and reproducing the image by a predetermined reproducing apparatus, a contour extracting step of extracting contour vector data along an edge of the input image, a resolution of the input image and the reproducing apparatus. And a smoothing step for smoothing the contour vector data extracted from the contour extracting step according to the comparison result of the comparing step, and the contour vector data smoothed by the smoothing step. And a generation step of generating a recorded image based on the above.

[0006]

In the structure or process of the present invention, the contour vector data along the edge of the input image is extracted. Then, the resolution of the input image and the recording resolution of the reproducing apparatus are compared, the contour vector data extracted based on the comparison result is smoothed, and a recorded image is generated based on the smoothed contour vector data.

[0007]

Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

<Description of Device Configuration> FIG. 1 is a block diagram of the image processing communication device of the embodiment. In the figure, reference numeral 100 denotes an image scanner which A / D-converts image data read in a raster scanning order by a photoelectric conversion device such as a CCD, and further binarizes the A / D-converted digital multi-valued data. It is binarized by and output to the bus A1500 as binary raster image data. Bus A
The binary raster image data output to the
Stored in 300.

Reference numeral 200 denotes an image area separation circuit, which is multi-valued data of raster scanning input from the image scanner 100 (for example, in the case of 256 gradations of one pixel, 8 bit / pixel).
1) is input, the halftone area and the character / line drawing area are separated, and an image area separation table (details described later) for each image area is created in the memory A300. It should be noted that which part of the read image is a binary image such as a character or line drawing and which part is a halftone image can be determined by examining the value of the input multi-valued data. That is, in general, a binary image literally has only two states of white (lowest density) and black (highest density), so that the density change in a region (edge) where these two states are adjacent is sharp. . On the other hand, since the density of the halftone image gradually changes, the density change becomes gentle. Therefore, by examining this density change, it becomes clear whether the pixel position of interest is at the edge of the binary image or at the edge of the halftone image.
Note that such a technique for distinguishing a binary image such as a character / line drawing from a halftone image is already known, and may be realized by other processing. Further, the operator may instruct the type of the read document or the like.

Reference numeral 700 denotes a contour extraction circuit which reads the binary raster image data stored in the memory A300 and an image area separation table for image area separation if necessary, and a memory B11.
A contour coordinate data string is created at 00.

Reference numeral 800 denotes a coding / decoding circuit, which reads the binary raster image data accumulated in the memory A300 and performs coding compression of the binary image such as MH, MR, MMR when performing the coding process. The encoded image data is stored in B1100. When performing the decryption process, the memory B
The encoded image data accumulated in 1100 is input, and the decoded binary raster image data is output to the memory A300.

Reference numeral 900 denotes a smoothing / coordinate conversion circuit, which inputs the contour coordinate data string accumulated in the memory B1100, and performs various coordinate conversions (multiplication of magnification, x-coordinate y-coordinate exchange) and enlargement / magnification contouring. The smoothing process for smoothing the jagged edges is performed, and the converted contour coordinate data string is created in the memory B1100.

A communication control circuit (CCU) 1300 inputs the image data (contour coordinate data string or image coded data and, if necessary, an area separation table) stored in the memory B1100, and inputs the image data to the communication line. Is output. In addition, the image data received from the communication line is stored in the memory B.
Accumulate at 1100.

Reference numeral 1000 denotes a binary image regenerating circuit, which inputs a contour coordinate data string accumulated in the memory B1100, draws a contour line in the memory A300 based on the contour coordinate data, and outputs a binary raster image (bitmap). Image).

Reference numeral 400 denotes an intermediate coating circuit, which inputs a binary raster image (bitmap image) in which a contour line is drawn in the memory A300, performs intermediate coating in the closed contour area, and stores it in the FIFO memory 500. And output to.

The FIFO memory 500 regains horizontal synchronization and vertical synchronization with the printer and outputs binary raster image data to the printer 600.

Reference numeral 600 is a printer such as LBP, which is a FIFO 5
At 00, the binary raster image data resynchronized is input and the image data is recorded on the recording paper.

<Description of Processing Content> Next, the flow of image data of the image processing communication apparatus according to the present embodiment will be described with reference to the flowchart of FIG. 2 for the transmitting operation, FIG. 3 for the receiving operation, and FIG. 4 for the copying operation. Each will be described in detail.

<Description of Transmission Process> First, the processing procedure of the transmission operation will be described with reference to the flowchart of FIG.

In the image reading in step S1, the image is read by the image scanner 100 as binary raster image data, transferred to the memory A300 and stored therein.
At this time, if the image data other than the immediate transmission is not executed immediately, that is, if the image data transmission is not executed immediately, in order to effectively use the memory, the memory A300 is set as shown in steps S9, S10, and S11.
The image data stored in (1) is encoded and compressed by the encoding / decoding circuit 800, stored in the memory B1100 as an image file, and decoded at the time of transmission to be expanded in the memory A300 as a binary raster image. At the same time when the binary raster image is stored, the multi-valued raster image data from the image scanner 100 is output to the image area separation circuit 200. The image area separation circuit 200 determines for each block (predetermined area) whether it is a character / line drawing area or a halftone area in the image, and creates an area determination table indicating the characteristics of the image area in the memory A300. Of course, the accumulated encoded image data file and the area determination table file have the same file attributes and are taken out when necessary.

At this time, it is clear whether the pseudo halftone is used or not by pressing the selection button (halftone button provided on the operation unit (not shown)) as to whether the pseudo halftone processing is performed during binarization. In this case, the image area separation table for each image area is not created, and only the image attributes of one page of pseudo halftone or character / line drawing may be recorded.

In step S3, the area determination table of the character / line drawing area or the pseudo halftone area is stored in the memory A.
Read from 300, and if it is a character / line drawing area, step S
4, if it is a halftone region, the process branches to step S12.
If it is determined that the image is in the halftone region, and the process proceeds to step S12, and it is determined that variable magnification is necessary, then it is 2 as in the conventional G3 and G4.
After the scaling process for each raster, which is the scaling process of the value raster image,
The image data is transmitted after being encoded according to the communication line.

When transmitting the image area determination table at this time, the area determination table of the memory A300 is transferred to the memory B1100 and transmitted.

In step S4, when the receiving side has a function of regenerating the binary raster image from the contour coordinate data sequence as image data and it is judged that the contour coordinate data sequence can be transmitted, that fact is received. Is notified to the transmitting side and the process proceeds to step S5. If the receiving side is configured only with the conventional G3 or G4 function and cannot receive the contour coordinate data string, the process proceeds to step S16.
In step S16, it is determined whether or not the scaling is necessary, and if it is necessary, the process proceeds to step S17, and thereafter, the scaling process is performed using the contour coordinate data string. If the scaling is not necessary, the process proceeds directly to step S23 and is transmitted after the encoding process.

In step S17, the binary raster image data stored in the memory A300 is input to the contour extraction circuit 700, the binary raster image data is converted into a contour coordinate data string, and then the contour coordinate data is stored in the memory B1100. Accumulate columns. In step S18, it is determined whether or not the enlarging process is necessary for the contour coordinate data string stored in the memory B1100. If the enlarging process is necessary, the process proceeds to step S19, and if not, the process proceeds to step S20.

In step S19, a contour coordinate data string is input from the memory B1100, a contour smoothing process described later is performed, and the process proceeds to step S20. In step S20, each coordinate value is multiplied by a scaling factor to be converted into a coordinate value according to the transmission resolution. In step S21, the contour coordinate data string converted to the binary image regenerating circuit 1000 is transferred from the memory B1100, and a contour line is drawn on the bitmap image in the memory A300. In step S22, the image bitmap in which the contour line is drawn in the intermediate coating circuit 400 is fetched for each raster and is expanded in the memory A300 as binary raster image data in which intermediate coating is performed.

In step S23, the coding / decoding circuit 800 performs coding suitable for the communication mode and transfers the data to the memory B1100. The encoded image data transferred to the memory B1100 is CCU1300 in the case of G4.
Sent by. MODEM not shown for G3
Sent by.

The processing after step S5 will be described. If the image area to be transmitted is a character / line drawing and the receiving side can receive the contour coordinate data, the process proceeds to step S5. A contour extraction circuit 70 as a character / line drawing area
The image data transferred from the memory A300 to 0 is scanned for the entire image while updating a rough contour coordinate data table, which will be described later, and finally converted into a contour coordinate data string and stored in the memory B1100. In step S6, it is determined whether or not the scaling of the image data converted into the contour coordinate data string is necessary. If necessary, proceed to step S7 and store in memory B
The image data stored in 500 is transferred to the smoothing / coordinate conversion circuit 800, and the coordinate value is multiplied by the scaling factor. At this time, if necessary, the coordinate sequence is traced so that the feature points remain in the contour coordinate data sequence, and smoothing conversion is performed for the enlargement processing. If it is determined that the image can be restored by smoothing by tracing, the number of significant digits of the coordinate value of the coordinate data is reduced to compress the data amount. After the processing means, the contour coordinate data string coordinate-converted by the smoothing / coordinate conversion circuit 900 is returned to the memory B1100. In step S8,
Image data whose transmission resolution and reception resolution match is CCU
Sent by 600. In the case of G3, it is similarly transmitted by a MODEM (not shown).

By the way, considering the communication error of the image data, when the communication device is a G4 CCU and the image is to be communicated as a contour coordinate data string, protocol error correction and resending of the error image cause the contour coordinate data string to be transferred. Is it possible to send and receive? E for G3 using MODEM
Data transmission / reception using HDLC for CM is required. Therefore, when transmitting and receiving the contour coordinate data string through MODEM by G3 and using the conventional telephone line, compulsory E
When the CM mode is set and the frequency of ECM retransmission is high depending on the line status, or when ECM transmission / reception cannot be performed, the image data transmission is switched to the conventional MH and MR code, and the image communication is performed in the conventional G3 mode. To do.

<Description of Reception Processing> Next, the reception processing of this apparatus will be described with reference to the flowchart of FIG.

In step S101, the CCU 13 is received.
00 or image data is received from a MODEM (not shown). The received image is coded image data such as MH and MR according to conventional G3 or MMR according to G4, or a contour coordinate data string transmitted by the image processing communication device described in the embodiment. The received image data is temporarily stored in the memory B1100.

In step S102, it is determined whether or not the received image data is the contour coordinate data string transmitted from the image processing communication device.

If it is determined that the image data is the image data received from the apparatus described in the embodiment, the process branches to step S114, and the MH, MR,
If it is determined that the data is MMR code data, step S103
Proceed to.

In step S114, it is determined whether the received image data needs to be scaled. If it is determined that the scaling processing is necessary, the process proceeds to step S107, and thereafter, the scaling processing using the contour coordinate data string is performed. If the scaling process is not necessary, the process proceeds to step S109, where the scanning direction coincidence determination is performed, and thereafter, the image data from the contour coordinate data string
Value raster image data is restored and printed.

Further, the received image data is MH, MR, M
When it is determined that the image data is MR-encoded image data and the process proceeds to step S103, the received data is sent to the encoding / decoding circuit 800, is decoded into binary raster image data, and is stored in the memory A300. Accumulated in. In the next step S104, it is determined whether or not the scaling is necessary when the received image data is printed out. If it is determined that the scaling is necessary, the process proceeds to step S105. A300 to FIFO500
Then, the binary raster image data is transferred to the printer 600, is synchronized with the printer 600 again, and is printed out from the printer 600.

In step S105, it is determined whether the received image data is a pseudo-halftone image or a character / line drawing image based on the region determination (image attribute or region determination table). Then, for the pseudo halftone image data block, the process proceeds to step S116, and the raster image scaling circuit 160
It is transferred to 0 and scaled as a binary raster image. Also,
The image block determined to be the character / line drawing area is transferred to the contour extraction circuit 700 and subjected to scaling processing as a contour coordinate data string described below.

In step S106, the binary raster image data of the character / line drawing stored in the memory A300 is transferred to the contour extracting circuit 700, converted from the binary raster image data into a contour coordinate data string, and stored in the memory B1100. It

In step S107, it is determined whether the sub-scanning or the main scanning is the enlargement process. If it is the enlargement process, the process proceeds to step S115, and the memory B110
The contour coordinate data string accumulated in 0 is transferred to the smoothing / coordinate conversion circuit 900, and the first smoothing process and the second smoothing process are performed by the tracking pattern matching of the contour coordinate data string, which will be described later. Smooths coordinate data. By this processing, the jaggedness of the oblique line at the time of enlargement is suppressed.

In step S108, the contour coordinate data string or the contour smoothed contour coordinate data string is converted into coordinate data matching the resolution of the print output by multiplying each coordinate string by a scaling factor.

In step S109, it is determined whether or not the scanning direction of the image data is different from the image scanning direction at the time of recording, for example, when the image read in the vertical direction of B5 is output in the horizontal direction of A4. In this case, the process proceeds to step S110, and the x coordinate and the y coordinate of the contour coordinate data string are exchanged,
It is stored in the memory B1100. If the coordinates need not be exchanged, they are stored in the memory B1100 as they are.

In step S111, the memory B1100
The contour coordinate data string after pixel density conversion stored in is input to the binary image regenerating circuit, and a part of the memory A300 is used for storing the bitmap image of the output image.
Draw the outline of the bitmap image.

In step S112, the image data in which the contour line is drawn is fetched from the memory A300 for each raster, and the intermediate coating circuit 400 performs intermediate painting of the contour.
Transfer to FO500. At this point, the contour coordinate data is converted into binary raster image data again. Separately, the binary raster image accumulated in the memory A300 by branching in step S104 or step S105 is also fetched from the memory A300 at this point in the same manner as F
It is transferred to the IFO 500.

The binary raster image data transferred to the FIFO 500 is sent to the printer 60 in step S1013.
It is resynchronized with 0 and output from the printer 600 as a raster image image.

<Description of Copy Processing> Next, the processing contents at the time of copying will be described using the flowchart of FIG.

In step S201, the original image is read. In this case, if it is not necessary to store files like immediate copying, steps S202 to S213
The image data output from the image scanner 100 is transferred to the FIFO 500 via the memory A300 and printed out. The reason why the data is temporarily stored in the memory A300 is to absorb the difference in speed between the image scanner and the printer. If the recording speed can be changed as in a thermal printer, the data is directly transferred to the FIFO 500 as described above. And output it. In the case of immediate copying, if the reading resolution of the image scanner 100 is set to be the same as the output resolution of the printer, it is not necessary to perform any processing, and the transfer processing described above may be performed.

If it is instructed to temporarily store the image data as a file instead of the immediate copy and then perform the copy, the process proceeds to step S203, and the image file is encoded and stored to improve the memory efficiency. .. Here, it is assumed that the binary raster image stored in the memory A300 is transferred to the encoding / decoding circuit 800, converted into an MH code or the like, and transferred and stored in the memory B1100.
In addition, of course, various compression methods other than MH can be used for encoding and compression, and a compression method unique to this apparatus may be adopted. The image data once stored is read out from the memory B1100 again as shown in step S204 during the print output operation, and the encoding / decoding circuit 800
And is decoded as a binary raster image data in the memory A300.

In step S206, it is determined whether or not it is necessary to scale the stored image file. The basis of the determination here is when the document image size and the size of the apparatus are different, or when the operator gives an instruction. If the scaling is unnecessary, the process proceeds to step S213,
The image data is transferred to the FIFO 500 for each raster, is synchronized with the printer 600, and is printed out. When performing the scaling process, the process proceeds to step S207, and it is determined based on the region determination table whether the stored image file is a pseudo halftone image or a character / line image as shown in the transmission process. To do. In the case of a pseudo halftone image, the decoded image is transferred to the raster image scaling circuit 1600, and 2
The value raster image is scaled as it is and returned to the bitmap image memory of the memory A300. If it is determined that the block is the character / line-drawing image, the process proceeds to step S208, and the block determined to be the character / line-drawing area is extracted by the contour extraction circuit
The data is sequentially transferred to 0, the binary raster image data is converted into a contour coordinate data string, and stored as a memory B1100 contour coordinate data string. As described in the reception processing above, the standard resolution of G3 (main scanning 8 pel / mm, sub scanning 3.85 pe)
When performing enlarging processing such that the image data accumulated in 1 / mm) is output to a 400 dpi printer, step S
Since the smoothing process is performed at 214, the smoothing / coordinate conversion circuit performs the first smoothing process and the second smoothing process as described later.

In step S210, each coordinate value of the contour coordinate data string or the smoothed contour coordinate data string is multiplied by a scaling factor to be converted into a contour coordinate data string matching the resolution and size of the printer output image. .. In step S211, the image data converted into the outline coordinate data sequence of the printer output image is transferred to the binary image regenerating circuit 1000, and the binary image reproducing circuit 1000 draws an outline in the bitmap image memory of the memory A300. It In step S212, the memory A30
The binary raster image data with the contour line formed at 0 is read for each raster, transferred to the FIFO 500, and printed out in synchronization with the printer as shown in step S213.

The above processing is explained step by step, but of course, by performing each processing for each block, decoding processing, contour extraction processing, smoothing processing, coordinate conversion processing,
The binary image regeneration processing and the intermediate coating processing can be performed in parallel, and the system throughput can be increased. Further, in the present embodiment, the processing having a heavy load may be performed during the standby instead of during the transmission / reception.

<Description of Each Processing Circuit> Next, in order to explain the resolution conversion by the contour coordinate sequence in each processing block in detail, a contour extraction circuit, a smoothing / coordinate conversion circuit, and a binary image regenerated image circuit. The in-coat circuit will be described in detail with reference to the drawings.

<Contour Extraction Circuit> The contour extraction circuit 700 is
As shown in FIG. 6, the pixel of interest 611 in the binary image
And eight pixels (A, B, C, D, 0, 1,
The processing is advanced by observing the states of 2 and 3), and the pixel of interest is raster-scanned and the processing of the entire image is sequentially performed while shifting the pixel by pixel. Specifically, it is as follows.

The starting point of the rough contour vector extracted here
The position of the end point is assumed to be in the intermediate position between pixels in both the main scanning direction and the sub scanning direction. Further, in both the main scanning direction and the sub-scanning direction, the central position of a pixel is indicated by a positive integer, and the pixel position is represented by two-dimensional coordinates. For example, in an image of 1728 pixels in the main scanning direction and 2287 pixels in the sub scanning direction, when the position of the pixel of interest is now [3, 7] (meaning the third pixel position of the seventh raster), a rough contour surrounding it The vector coordinate sequence is clockwise (2.5, 6.5),
(3.5, 6.5), (3.5, 7.5), (2.5,
7.5). That is, it is the coordinate positions of the four corners when the pixel of interest is a rectangle. In this case, the rough contour vector is defined by the four points a, b, c and d, and the vector x →
Expressed in the y format, a → b, b → c, c → d, d → a.

FIG. 5 is a diagram showing internal blocks of the contour extraction circuit 700. An input control circuit 510 takes in the binary raster image data accumulated in the memory A 300 and outputs it as serial data. It should be noted that this data is output as serial data in synchronization with a horizontal and vertical synchronizing signal (not shown). Numerals 521 and 522 are FIFO memories for taking out pixel data over three lines in the vertical direction and delay line-by-line the pixel data input serially. Reference numeral 530 denotes a 3 × 3 shift register group, which receives an output from the input control circuit 510, an output delayed by one line from the FIFO 521, and an output delayed by two lines from the FIFO 522, and outputs data of three lines. Enter sequentially. Then, the input binary image data of three lines is shifted by one pixel, and the three lines as shown in FIG.
The data of × 3 pixels is output to the decoder 540. The decoder 540 outputs 4-bit numerical data indicating the state of the surrounding 8 pixels excluding the pixel of interest (here, x in FIG. 6) and the value of the pixel of interest to the contour extraction calculation circuit 570. The state of the surrounding 8 pixels is information indicating the state in which the pixel of interest is placed. For example, whether the pixel of interest is at the edge of the binary image, and if it is at the edge, It shows which of the left and right directions is white (binary data is “0”).

A main scanning counter 550 outputs the pixel position of the target pixel in the main scanning direction to the contour extraction calculation circuit 570. A sub-scanning counter 560 outputs the pixel position of interest in the main-scanning direction to the contour extraction calculation circuit 570.

The contour extracting / calculating circuit 570 includes a decoder 54.
A rough contour vector is extracted from the output value from 0, and the coordinates of the starting point of each rough contour vector and another rough contour vector that flows into this rough contour vector (the coordinates of the starting point of this vector are the end points) A table having item number information of another rough contour vector flowing out from this rough contour vector (coordinates of the end points of this vector being the starting point) is created and updated.

The above-mentioned vector will be described below.

In the embodiment, the vector along the edge of the binary image is extracted, but if the vector is extracted in consideration of the pixel level, it can be divided into a vector in the vertical direction and a vector in the horizontal direction. In other words, the edges of the binary image are a collection of vertical and horizontal vectors. In addition, when paying attention to a certain vertical vector, the horizontal vector is always connected to the start point and the end point of the vector, that is, the vertical vector is sandwiched between the horizontal vectors. On the contrary, a certain horizontal vector is sandwiched by vertical vectors. In the embodiment, when a certain vector is noticed, it is connected to the starting point of the vector, that is, the vector in which the starting point position of the attention vector is the ending point is called the inflow vector, and the vector whose starting point is the ending point of the attention vector Is called the outflow vector. Then, if the connection relation of the individual vectors is obtained in this way, the contour along the edge of the target binary image can be specified. It should be noted that each vector is provided with a unique number for identifying each vector, and the connection relationship between the vectors is clarified by the number.
The number that identifies each vector is called an item number.

FIG. 7 is a diagram showing a horizontal rough contour vector, and FIG. 8 is a diagram showing a vertical rough contour vector.
These are stored in the memory B1 as a table as described above.
It is stored in 100.

In the figure, 710 is a counter indicating the item number of the horizontal rough contour vector, which is incremented by 1 each time the horizontal rough contour vector is increased by 1 (newly discovered). 7
Reference numeral 21 is an area used to record the x coordinate of the starting point of the horizontal rough contour vector, and 722 is an area used to record the y coordinate of the starting point of the horizontal rough contour vector. Also, 723 is an area for storing the item number of a vertical vector (outflow vector) connected to the start point of this horizontal vector, and 724 is a diagram showing the item number of a vertical vector (outflow vector) to which the end point of this horizontal vector is connected. Is. Again, since the two vectors connected to the horizontal vector are vertical vectors, the area numbers 723 and 724 store the item numbers of the vertical vectors connected to the horizontal vector of interest.

This idea is the same for the vertical vector table shown in FIG. That is, 810 is a counter indicating the item number of the vertical rough contour vector, which is incremented by 1 each time the vertical rough contour vector is increased by one. Reference numeral 821 denotes an area used to record the x-coordinate of the starting point of the vertical rough contour vector, and 822 is an area used to record the y-coordinate of the starting point of the vertical rough contour vector. 823 is the item number of the horizontal vector (inflow vector) connected to the starting point of this vertical vector, 824
Is an area used to record the item number of the horizontal vector (outflow vector) to which the end point of this vertical vector is connected.

In these horizontal and vertical coarse contour vector tables, the rough contour vector is added and the contents of each table are updated every time one pixel is processed. And a vertical rough contour vector table.

Thus, by tracing the inflow and output vector item numbers of the horizontal and vertical direction rough contour vector tables shown in FIGS. 7 and 8, the total number of contour lines in the image as shown in FIG. A table of a rough contour vector coordinate sequence expressing the total number of contour lines for each line (contour closed loop), the x coordinate and the y coordinate of each point in the contour line is created, and a series of processing is ended.

In order to improve the processing speed, the table is not updated substantially when it is determined that the position of the pixel of interest is not at the edge of the image. Therefore, the vector table is added under such a situation. -The update process may not be performed.

Here, a concrete example of the above-mentioned horizontal / vertical rough contour vector table creating / updating process will be described. To simplify the description, it is assumed that the read image has a size of 6 × 5 pixels and that a single pixel A and continuous pixels B and C exist as shown in FIG. Here, the coordinate positions (coarse contour vector coordinates) of the four corners of the pixel A are (2.5, 2.
5), (2.5, 3.5), (1.5, 3.5),
(1.5, 2.5). The pixels B and C need not be described.

When this image is read and processed, black pixels are not detected until the third raster and the second pixel. At this time, all the pixels around the target pixel (pixel A) are white (“0”) pixels, and four vectors exist. That is, two in the horizontal direction and two in the vertical direction. In the embodiment, each time a new rough contour vector is generated, an item number is added to the vector, so in this case, item numbers 0 and 1 are given in the horizontal and vertical directions. Therefore, the horizontal / vertical vector table is in the state shown in FIG. The way to read this table is as follows.

Attention is now paid to the horizontal vector whose item number is "0". The vertical vector of the item number “1” flows into the starting point (upper left corner of the pixel A) of this attention vector,
It shows that the vertical vector of the item number “0” is flowing out from the end point of interest. The item number of each vector may be considered as an offset address indicating the position stored in the table. That is, it can be seen that the vertical vector data that flows in and out of the horizontal vector of item number "0" exists at offsets "0" and "1" in the vertical vector table.

Now, returning to FIG. 23, the pixel A is moved to the right next to it, but since the pixel of interest is white, the process proceeds to the next pixel B without doing anything.

When attention is paid to this pixel B, it can be seen that there are vectors in the vertical direction and the left direction except the right side. Moreover, the upper left corner of the pixel of interest is the starting point of the horizontal vector,
It can be seen that the coordinate position of the lower left corner can be treated as the start point of the vertical vector. Therefore, these points can be newly registered in the horizontal / vertical vector table. However, since "1" has already been used as the item number in both the vertical and horizontal directions, the coordinates (3.5, 2.5) of the upper left corner of the pixel of interest are set as the starting point of the horizontal vector of the item number "2". The coordinates (3.5, 3.5) of the lower left corner are stored as the starting point of the vertical vector of item number "2". Then, when focusing on the horizontal vector of the item number “2”, the vector flowing into itself is the vertical vector of the item number “2”, and the vertical vector flowing out is not known at this point (pixels continuing in the horizontal direction). Mark is present so that it can be distinguished from The same applies to the vertical vector of the item vector “2”. In this way, each table is updated as shown in FIG.

Now, when the processing advances to the pixel C, the coordinate positions (5.5, 3.5) and (5.
5, 2.5) occurs. Therefore, the table is updated at that coordinate position. At this time, the vertical vector that has not been determined yet and flows out from the horizontal vector of the item number “2” is the vertical vector of the item number “3” newly registered this time. Write. The vertical vector is updated in the same manner. In this way, each table is updated as shown in FIG. Then, when the horizontal and vertical vectors of all the rough contour vectors and their connection relationships are extracted,
A vector table as shown in FIG. 9 is created based on these vector tables.

FIG. 21 shows an example of the input image, and FIG. 22 shows a vector table obtained from the input image.

<Smoothing / Coordinate Conversion Circuit> Next, the smoothing / coordinate conversion circuit 900 in the embodiment will be described. The smoothing / coordinate conversion circuit 900 of the embodiment, as shown in FIG.
First smoothing circuit 910, first smoothing conversion table 94
0, a second smoothing circuit 920, and a coordinate conversion circuit 930.

In the first smoothing circuit 910, the rough contour data string converted data shown in FIG. 9 is fetched from the raster scanning binary image by the above-mentioned contour extracting circuit 700, and the coordinate string is traced for each vector closed area. While referring to the first smoothing conversion table based on the vector connection state, the contour coordinate data string is converted and the corner points are labeled.
The smoothed vertex coordinate data string and information on whether or not each vertex is a corner point are output. The second smoothing circuit 920 calculates a weighted average of coordinate values of a plurality of points before and after sandwiching the own point based on the first smoothed vertex coordinate data string and corner point information, and outputs a contour vector coordinate data string. .. In the coordinate conversion circuit 930,
If necessary, the x-axis and y-axis coordinate values are exchanged, and each coordinate value is multiplied by a scaling factor. Here, in the case of the reduction processing, the data is directly passed to the coordinate conversion circuit 930 after passing the smoothing processing of the first smoothing circuits 910 and 920.

Details of the above-mentioned processing will be described. In the first smoothing circuit 910, as shown in FIGS. 11 to 18, by referring to the patterns up to the front and rear three sides sandwiching the self side, the direction of each side
The rough contour coordinate numerical data sequence is removed and converted by referring to the pattern based on the length. Here, "N_" shown in FIG.
pnt "is the total number of closed loops of the rough contour coordinate numerical data,
The single circle is the start point of the horizontal vector and the end point of the vertical vector,
Triangles indicate the end point of the horizontal vector and the start point of the vertical vector, and the double circles indicate the corner points, respectively. Also, the first here
In smoothing, noise peculiar to binary image (notch / isolated point)
11 includes the pattern of FIG. That is, as shown in FIG. 11, in the removal of an isolated pixel of one pixel size, all the coordinate values are deleted. This prevents the pixel from being emphasized when the image is enlarged. Further, as shown in FIG. 12, in the case of storing a white hole in a black area, all the contour coordinate sequences are labeled as corner points, and the coordinate values are output as they are. The corner point here means that the coordinate position is immovable in the second smoothing process described later. In addition, although the description goes back and forth, in the embodiment, X, Y
Since the directions are rightward and downward, the leftward and upward directions are negative. In addition, for example, in FIG. 13 and the like, “≦ −” of “≦ −3” indicates that it continues in the negative direction, and “3” indicates that at least three pixels continue.

The meanings of FIGS. 11 and 12 are as described above, but a brief description of FIG. 13 and the following is as follows.

The meaning of FIG. 13 is a line segment having a width of 1 pixel, and the coordinate position representing the end of a fine line having a length of at least 3 pixels is defined as a corner point, and will be described later in the second section.
This means preventing the coordinate position from being changed by the smoothing process, in other words, preventing rounding. To make it easier to understand, in the background, a line segment having a length of 3 pixels or more and having a width of 1 pixel is recognized as a part of a character, a line drawing, or the like, not "dust" in the read image. It means that. However, here, the length is set to 3 pixels or more, but this depends on the reading resolution,
When the reading resolution is low, the length may be 2 pixels, and when the image is read at a higher resolution, the length may be 4 or more. This also applies to what will be explained below.

The meaning of FIG. 14 means that the unevenness of one pixel in a flat state for a predetermined length (3 pixels in the figure) is deleted, that is, the rough contour vector data of the unevenness is deleted. To do. FIG. 15 means that when the unevenness is present continuously, the unevenness is made flat.

FIG. 16 shows the definition of corner points and the concept of vector smoothing. However, in the figure, “D _i ” represents the rough contour vector of interest. For example, in the case of FIG. 9A, when the end point position of the rough contour vector of interest is in the illustrated state, it means that the end point position of the target rough contour vector is the corner point. In addition, the vector D _i-1 immediately before the vector of interest D _i is deleted, and the same length as the vector D _i-2 two before is taken from the start point of the vector of interest, and the end point position and the vector D _{i. The} vector connecting the starting point position of _i-2 is updated to D _i-2 . Further, the vector represented by the updated end point and corner point of D _i-2 is updated as the vector of interest.

FIG. 17 shows the contents of the smoothing processing for the gently shaded area. For example, as shown in FIG. 9A, for an edge inclined in a predetermined direction such that it goes up by 1 pixel, extends by 3 pixels or more in the horizontal direction, and goes up by 1 pixel again, the midpoint position of the attention vector is set to the immediately preceding vector D. The end point of _i-1 and the start point of the vector D _{i + 1} immediately after are set. This process is not performed when the inclination is in the upward direction and then in the downward direction.
This judgment can be understood by multiplying the gradient of the immediately preceding vector and the gradient of the immediately following vector and checking the sign. In addition, the same figure (B)
Shows an example in which five vectors are finally made into three vectors. That is, under the conditions as shown in the figure, the vector D before the smoothing is deleted by deleting the immediately preceding and subsequent vectors.
A vector obtained by connecting the starting point position of _{i-2 and} the point A on the vector D _{i of} interest is a vector D _i-2 , and a vector represented by points A and B is a vector of interest D _i , point A The vector represented by the end point of the vector D _{i + 2} before being smoothed with D _{i + 2}
And FIG. 18 is as illustrated.

Now, in the second smoothing circuit 920, as shown in FIG.
As shown in FIG. 3, the corner points indicated by double circles are left as they are, and the other coordinate points are weighted by the coordinate values of the plural points before and after the point (in the embodiment, the coordinate values of the two points before and after). The average is obtained, and the value is output as the vertex coordinate data string after the second smoothing. Here, the point Q _i shown in FIG. 19 indicates the vertex coordinate data string after the second smoothing, and the point P _i indicates the vertex coordinate data string after the first smoothing. In the example, Q ₁ (9 / 4,2) is changed to P ₀ (1,
3), P ₁ (2,2), P ₂ (4,1). Here, the number of effective digits used in the first smoothing and the second smoothing is arbitrarily set within a range effective for the recording resolution.

The coordinate conversion circuit 930 performs x-axis and y-axis coordinate conversion depending on the difference between the main scan of the processed image and the recorded image, and multiplies each coordinate sequence by a scaling factor in accordance with the scaling process.

For example, the input image is scanned in both main scanning and sub scanning.
When multiplying, the x-coordinate and the y-coordinate of the second smoothed vertex coordinate data string are both doubled, and the decimal places are rounded off to perform coordinate conversion.

The contour coordinate data string thus obtained in each of the circuits 910 to 940 is output to the memory B1100 and the processing is terminated.

<Binary Image Regenerating Circuit, Intermediate Coating Circuit> In this embodiment, the case of the page memory use type in which the bitmap image memory is used for one screen will be described. Of course, all the methods of converting the contour coordinate data sequence into a binary raster image image are effective.

In the binary image regenerating circuit 1000, the contour coordinate data string stored in the memory B1100 of FIG. 1 is read and the bitmap image memory 1 on the memory A300 is read.
Draw a contour line on the surface.

At this time, since the filling operation in the intermediate coating circuit in the subsequent stage can be performed at a high speed and the contour line is drawn with the bitmap image of one page, two to three consecutive line segment vectors (each of the contour coordinate series). Control the drawing method of contour pixels on the line segment vector of interest by referring to the line segment vector of interest and the state (direction) of the vector immediately before and immediately after that vector I will do it. The content of the control is to treat the end point on the line segment vector of interest and the point on the contour vector other than the end point separately, and not draw them, draw at the pixel position on the line segment vector, or Whether to draw by shifting the pixel on the line segment vector to the pixel position adjacent to the pixel by one pixel in the main scanning direction is determined. The actual contour pixel drawing operation is performed by EXORing the value already stored and 1 at the pixel position to be drawn.
It is executed by storing the result of taking. In any case, the contour is drawn so that the pixels can be switched on / off simply by sequentially reading the pixels in the main scanning direction. In addition, a proposal for such contour drawing is
It is assumed that the one already proposed by the applicant of the present application is adopted, and the detailed description thereof will be omitted.

In the intermediate coating circuit 400, after the outline drawing circuit has finished drawing all the outline edges, the outline drawing image in the bitmap image memory (memory A300) is raster-scanned at an arbitrary synchronization timing and read while The intermediate coating process is executed in the line process, and it is transferred to the bitmap image memory again. The intermediate coating process itself is processed by a circuit as shown in FIG.
DATA input in synchronism with is output to OUT while sequentially being black-and-white inverted in the contour drawing pixels.
Here, LSYNC is a line synchronization signal and is input as a synchronization reset signal at the start of raster pixel input. 5
A latch 10 holds the OUT output value one pixel before. 5
An EXOR 20 outputs an EXOR of the input data and the OUT output value of the immediately preceding pixel.

Here, except for the outline edge which is not drawn, the drawing of contour pixels on a straight line including the end points after processing is also executed by this half-painting circuit.

[Explanation of Other Embodiments] In the above embodiment, the image area separation circuit separates the character / line drawing image and the halftone image, but the image attribute is previously set by the mode select button of the image scanner or the communication protocol. If it is clear that the converted image is a pseudo-halftone image or a character / line drawing image, the region table by image area separation is not required, and it is possible to switch whether to perform pixel density conversion by contour extraction according to image attributes. You can go. Further, the pseudo-halftone image has a relatively small total number of points in one closed loop of the contour coordinate data sequence and the vector direction changes frequently within one closed loop as compared with the character line drawing image.
At the stage of performing the smoothing process instead of 0 and the region determination table, a simple image area separation function can be realized by switching whether to perform the smoothing process depending on the total number of 1 closed loop of the contour coordinate data string. Specifically, the processing is performed as follows.

That is, since the minimum and maximum points of the x, y coordinate points of all the vectors forming one closed loop can be obtained, the rectangle size circumscribing the closed loop can be determined. That is, it is possible to indirectly extract the size of the closed loop as a rectangular size. Therefore, it is possible to determine whether to perform smoothing, in other words, whether the closed loop is a halftone image or a character / line drawing image based on the relationship between the rectangular size and the total number of points forming the closed loop. become. In this case, the relationship between the rectangular size and the closed loop may be stored as a table or as an expression.

Further, in this embodiment, since the enlargement / reduction processing and the encoding processing by the contour coordinate data string and the enlargement / reduction processing by the conventional binary raster image are both included, the data size of the contour coordinate data string and the MH. , MR, and MMR encoded data are compared with each other, and the image data having the smaller data amount is transmitted, whereby the communication time can be efficiently shortened.

Since the contour coordinate data string is considerably large depending on the image, there is a possibility that the memory overflows when the contour coordinate data string is extracted depending on the image, such as when the memory B1100 has a small capacity. In this case, the contour extraction process may be stopped and switched to the coordinate conversion (magnification) process using the binary raster image. That is, the memory B110
Since the capacity of 0 is known in advance, it is sufficient to compare the final address position of the rough contour vector table being constructed with the final effective address position of the memory.

In addition to the scaling by the coordinate conversion, it is also possible to multiply the scaling ratios for the main scanning and the sub-scanning separately, and it is possible to perform the x-axis and the y-axis independently. In such processing, the input original image size is compared with the paper size for print output, and the x-axis scaling factor and the y-axis scaling factor may be calculated according to the size difference. Of course, the user (operator) may arbitrarily set it according to his / her preference. The x- and y-axis scaling factors may be processed by the sender by negotiation, or may be processed when the data received by the receiver is printed.

Further, in the smoothing process, in the above embodiment, the black isolated points and the notches are removed to remove dust pixels, but the image data read in the standard resolution of G3 standard is Since notches and isolated points are often necessary for character interpretation information, patterns for notch removal and isolated pixel removal depending on the resolution of the input image in an external switching mode (for example, a switch to that effect is provided on an operation panel (not shown)). Can be removed from the smoothing pattern and processed. Of course, it is possible to easily switch between smoothing processing and non-smoothing processing according to preference with the external mode key.

In the coordinate conversion circuit 900 according to the present embodiment, only the x-coordinate and the y-coordinate are exchanged and the multiplication of the magnification is performed, but at the time of this processing, the output value of the skew angle detection device for the read document (not shown) is used. By performing coordinate rotation by affine transformation of the contour coordinate data sequence, it is possible to correct the skew of the read document. In this case, for example, FIG.
As shown in, convey the read document in the sub-scanning direction,
Alternatively, when the scanner is moved in the sub scanning direction for reading, the edge position of the document in the main scanning direction may be sequentially detected. That is, as shown in the figure, the deviation amount lx when one document is read and the conveyance amount ly in the sub-scanning direction at that time are detected. Therefore, the skew angle θ of the document is detected.
Is calculated as tan ^-1 (ly / lx).

Various means can be considered as means for detecting a change in the edge position of the document. For example, when a document is conveyed and its recording surface is read, the background color (the color detected when there is no read document) at the reading position is set to a color other than white. In general, the background color of the document itself is white, and if it can be distinguished from the white color, the edge can be detected. In addition, a pressing plate that presses from the lateral direction of the document conveyance direction with a small force that does not bend the document and is movable in the left and right (main scanning) directions is provided for the document conveyance amount. The degree of skew may be detected by detecting the amount of movement on the left and right.

In the skew correction processing, the original image is read, and after the read image is stored in the memory A300, or when the read image is stored, the image is rotated in the reverse direction by the obtained skew angle (affine transformation). You can do it. After that, the above-mentioned processing may be performed. Moreover, you may perform a rotation process with respect to the coordinate data obtained by performing the above-mentioned 2nd smoothing process. In addition, when skew correction is performed, such processing may be automatically performed, but the operator is notified of that fact (a message is displayed on the display unit provided on the operation panel, etc.), and the operator performs skew correction. You may make it instruct | indicate whether it corrects.

Further, regardless of the skewed reading of the original image, the operation panel may be instructed to rotate at an arbitrary angle. That is, it is provided in case the characters of the document to be read are already skewed.

In the binary image regenerating circuit, the case of the page memory use type in which the image memory of the bitmap is used for one screen has been described. However, as in the scan line conversion (bucket sort method), the edge table and the active edge table are used. It is also possible to draw the ridge line edge of the contour image by using a line buffer of several lines.

In this embodiment, the printer is used as the image output device, but the FIFO 500 and printer 600 of FIG.
Instead of, a video memory and a display can be used to output the image to the display.

As an application example of communication using the contour coordinate data string, a digitizer showing the image position is separately provided,
It is also possible to add a decoration code (change of pattern of shading or color painting, change of color) to the contour coordinate data closed loop in the area designated by the digitizer and send it. On the receiving side, it is possible to easily change the pattern of shading or the color painting and the color change according to the decoration code.

Further, instead of once expanding and transmitting a font as a binary raster image like a report or a header, it is directly transmitted / received as font data using an outline or a conventional outline expansion is used to regenerate a binary image. It is also possible to facilitate the output of the outline font by using it in common with the intermediate coating circuit.

Of course, in the present embodiment, all the operations used for the conventional resolution conversion can be realized, and arbitrary scaling processing by a magnification designation key and processing for putting a long original on a standard cut sheet by cassette size detection. Can be realized by the configuration of this embodiment.

As described above, according to this embodiment, even when the original is skewed and read, the skewed portion is reversely rotated and corrected, so that an erect and good image is obtained. Will be able to obtain.

In addition to handling the bit image of the original image, the contour vector is extracted and processed based on the extracted contour vector, so that the edge is not jagged.

Further, since the data based on the extracted contour vector is transmitted to the other party and the other party reproduces and outputs the image based on the received data, the communication time can be shortened and a high-definition image can be displayed. Transmission becomes possible.

Further, since the contour vector extracted from the original image is smoothed, even if the enlargement process is performed, the vector is enlarged and the image is reproduced, so that a high-quality image can be obtained regardless of the magnification. Will be possible.

Further, since the scaling processing of the extracted contour vector is performed only when the resolution conversion is required, the load on the system can be minimized and the normal processing speed without the scaling processing is reduced. It becomes possible to prevent that.

When the contour vector is extracted from the read binary image, it is determined whether the storage size of the contour vector exceeds the memory capacity. If it is determined that the memory is over, the contour vector extraction processing is immediately performed. Then, the processing is switched to the processing using the binary image. This makes it possible to correctly print or send even when the memory is full.

When performing the scaling processing based on the contour vector data, whether or not the smoothing processing is performed is switched by an external switch. As a result, it is possible to switch between smoothing processing and emphasis on processing speed according to operator preference. Furthermore,
When the read or received image is scaled and printed, a smoothing process is performed to obtain a high-quality image with less distortion. Moreover, if the scaling factor is designated by a switch (not shown), an image of a desired size can be obtained. Further, since the scaling processing based on the contour vector data is performed only when the enlargement processing is performed, it is possible to reduce the load on the apparatus and prevent the processing speed from being reduced when performing processing such as equal magnification or reduction. It will be possible.

Further, since it is possible to determine to some extent whether the image is a halftone image or a character / line drawing image based on the total number of points for the extracted closed loop, it is possible to omit the device and circuit relating to the region determination, and reduce the cost. It is possible to measure down.

The scaling process based on the contour vector is
It is effective only for character and line drawing images, and when it is applied to halftone images, good results cannot be obtained. In this respect, according to the above-described embodiment, the scaling processing based on the contour vector data obtained only for the character / line drawing image is performed, and the scaling for the halftone image is performed by interpolation of the pixels forming the image. Since it is decided to perform the thinning process or the thinning process, it is possible to obtain a good image.

In the communication between the devices described in the embodiments, the data to be communicated can be contour coordinate data, and the transmission side or the reception side can change the magnification of the data in the x and y directions. It can be performed independently, and it is possible to obtain a good image according to one's own taste even if such scaling is performed.

The present invention may be applied to a system composed of a plurality of devices or an apparatus composed of a single device. Further, it goes without saying that the present invention can be applied to the case where it is achieved by supplying a program to a system or an apparatus.

[0114]

As described above, according to the apparatus or method of the present invention, when an input image is reproduced by a predetermined reproducing apparatus, it is possible to reproduce a high quality image according to the reproducing apparatus. Become.

[Brief description of drawings]

FIG. 1 is a block configuration diagram of a facsimile apparatus of this embodiment.

FIG. 2 is a flowchart showing the contents of transmission processing.

FIG. 3 is a flowchart showing the contents of reception processing.

FIG. 4 is a flowchart showing the contents of copy processing.

FIG. 5 is a block configuration diagram of a contour extraction circuit in the embodiment.

FIG. 6 is a diagram for explaining raster image scanning in a contour extraction circuit.

FIG. 7 is a diagram for explaining a horizontal rough contour vector table.

FIG. 8 is a diagram for explaining a vertical rough contour vector table.

FIG. 9 is a table of contour coordinate data strings.

FIG. 10 is a block configuration diagram of a smoothing / coordinate conversion circuit in the embodiment.

FIG. 11:

FIG. 18 is a diagram for explaining a first smoothing process in the example.

FIG. 19 is a diagram for explaining a second smoothing process in the example.

FIG. 20 is a block diagram of an intermediate coating circuit.

FIG. 21 is a diagram showing an example of an input image.

22 is a diagram showing an example of a contour coordinate data string for the image of FIG. 21. FIG.

FIG. 23 is a diagram showing a specific image example for explaining the processing content of rough contour vector extraction in the embodiment.

FIG. 24 is a diagram for explaining a process of constructing a rough contour vector table.

FIG. 25 is a diagram for explaining the principle of detecting the degree of document skew.

[Explanation of symbols]

 100 Image Scanner 200 Image Area Separation Circuit 300 Memory A 400 Intermediate Coating Circuit 500 FIFO 600 Printer 700 Contour Extraction Circuit 800 Code Decoding Circuit 900 Smoothing / Coordinate Conversion Circuit 1000 Binary Image Regeneration Circuit 1100 Memory B 1200 CPU 1300 CCU 1400 Bus B 1500 Bus A 1600 Raster image scaling circuit

[Procedure amendment]

[Submission date] December 4, 1992

[Procedure Amendment 1]

[Document name to be amended] Statement

[Name of item to be corrected] Brief description of the drawing

[Correction method] Change

[Correction content]

[Brief description of drawings]

FIG. 1 is a block configuration diagram of a facsimile apparatus of this embodiment.

FIG. 2A is a flowchart showing the contents of transmission processing.

FIG. 2B is a flowchart showing the contents of transmission processing.

FIG. 2C is a flowchart showing the contents of transmission processing.

FIG. 3A is a flowchart showing the content of a reception process.

FIG. 3B is a flowchart showing the content of a reception process.

FIG. 4 is a flowchart showing the contents of copy processing.

FIG. 5 is a block configuration diagram of a contour extraction circuit in the embodiment.

FIG. 6 is a diagram for explaining raster image scanning in a contour extraction circuit.

FIG. 7 is a diagram for explaining a horizontal rough contour vector table.

FIG. 8 is a diagram for explaining a vertical rough contour vector table.

FIG. 9 is a table of contour coordinate data strings.

FIG. 10 is a block configuration diagram of a smoothing / coordinate conversion circuit in the embodiment.

FIG. 11 is a diagram for explaining a first smoothing process in the example.

FIG. 12 is a diagram for explaining a first smoothing process in the embodiment.

FIG. 13 is a diagram for explaining a first smoothing process in the example.

FIG. 14 is a diagram for explaining a first smoothing process in the example.

FIG. 15 is a diagram for explaining a first smoothing process in the example.

FIG. 16 is a diagram for explaining a first smoothing process in the example.

FIG. 17 is a diagram for explaining a first smoothing process in the example.

FIG. 18 is a diagram for explaining a first smoothing process in the example.

FIG. 19 is a diagram for explaining a second smoothing process in the example.

FIG. 20 is a block diagram of an intermediate coating circuit.

FIG. 21 is a diagram showing an example of an input image.

22 is a diagram showing an example of a contour coordinate data string for the image of FIG. 21. FIG.

FIG. 23 is a diagram showing a specific image example for explaining the processing content of rough contour vector extraction in the embodiment.

FIG. 24 is a diagram for explaining a process of constructing a rough contour vector table.

FIG. 25 is a diagram for explaining the principle of detecting the degree of document skew.

[Explanation of Codes] 100 Image Scanner 200 Image Area Separation Circuit 300 Memory A 400 Intermediate Coating Circuit 500 FIFO 600 Printer 700 Contour Extraction Circuit 800 Code Decoding Circuit 900 Smoothing / Coordinate Conversion Circuit 1000 Binary Image Regeneration Circuit 1100 Memory B 1200 CPU 1300 CCU 1400 Bus B 1500 Bus A 1600 Raster image scaling circuit

Claims (2)

[Claims] 1. An image processing apparatus for inputting image data and reproducing the image by a predetermined reproducing apparatus, a contour extracting means for extracting contour vector data along an edge of the input image, and a resolution of the input image. A comparing means for comparing the resolutions of the reproducing device; a smoothing means for smoothing the contour vector data extracted by the contour extracting means in accordance with the comparison result of the comparing means; and a smoothing means smoothed by the smoothing means. An image processing apparatus comprising: a generation unit configured to generate a recorded image based on contour vector data. 2. An image processing method for inputting image data and reproducing the image by a predetermined reproducing apparatus, wherein a contour extraction step for extracting contour vector data along an edge of the input image, and a resolution of the input image. A comparison step of comparing the resolutions of the playback devices, a smoothing step of smoothing the contour vector data extracted from the contour extraction step according to the comparison result of the comparison step, and a smoothing step of smoothing the smoothing step. An image processing method, comprising: a generation step of generating a recorded image based on contour vector data.