JP4186558B2 - Image processing method and apparatus - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a technique for processing an image, and more particularly, to a technique for performing image processing that involves binarization processing for a photographic image.
[0002]
[Prior art]
In recent years, with the spread of digital cameras and the low cost of image processing software that handles images taken with digital cameras, photo images can be modified, trimmed, etc. Image processing, such as compositing with photos and clip art, has become possible.
[0003]
In addition, printers that easily realize photo-quality printing have become widespread, and it is easy to print an image after image processing as it is. For this reason, in the field of image processing, it is widely used by users without special knowledge, rather than image processing by professionals in the printing field such as photosetting and offset printing. For example, application software for the general public has been released for the purpose of composing a family photo and New Year's characters on a New Year's card or posting a photo and a map on a move notification. For such a purpose, there are, for example, the following patent documents regarding techniques for extracting an image from a photograph.
[Patent Document 1]
Japanese Patent Laid-Open No. 10-243211
[0004]
[Problems to be solved by the invention]
However, although such image processing using a photographic image was originally felt to be novel, the impression given to the viewer becomes thinner as it becomes widespread. Rather, the impression given to the viewer may be stronger than a casual picture of a picture letter or an illustration with a pen drawing than a picture that anyone can take. However, no one could easily draw illustrations.
[0005]
Therefore, filters that convert photographic images captured with digital cameras and scanners into illustrations have been proposed in the past, but simple edge extraction or simple processing to reduce the number of colors (so-called posterization) It was just enough to be used as a sketch for illustrations at best. It was impossible to use a photographic image converted as it is as an illustration.
[0006]
The apparatus of the present invention is intended to solve such problems and to process photographic images to obtain images that can be used as illustrations.
[0007]
[Means for solving the problems and their functions and effects]
An image processing method of the present invention that solves at least a part of the above problems is as follows.
An image processing method for inputting and processing a photographic image,
Select at least one of the photographic images recorded on the recording medium,
The selected photographic image is represented by parameters whose brightness and hue are independent,
The parameter representing the brightness is binarized by comparing with a predetermined threshold value,
Extracting the edge contained in the image from the photographic image,
By displaying the extracted edge superimposed on the image reproduced from the binarized parameter and the parameter representing the hue, the image is displayed as an illustration.
Is the gist.
[0008]
The present invention can be grasped as a program for realizing this method. Similarly, it can be grasped as a recording medium on which the program is recorded. Furthermore, it can be grasped as an invention of an apparatus corresponding to this method. The invention of such a device
An image processing apparatus for inputting and processing a photographic image,
Image selection means for selecting at least one of the photographic images recorded on the recording medium;
Binarizing means for representing the selected photographic image by a parameter whose brightness and hue are independent, and binarizing the parameter representing the brightness with a predetermined threshold;
Edge extraction means for extracting edges contained in the image from the photographic image;
Illustrator for displaying the image as an illustration by displaying the extracted edge superimposed on the image reproduced from the binarized parameter and the parameter representing the hue;
The gist is that.
[0009]
According to such an image processing method, a processing apparatus, or the like, at least one photographic image selected from photographic images recorded on a recording medium is expressed by a parameter whose brightness and hue are independent, for example, a YCrCb color space, Among these, a parameter representing brightness is binarized by comparing with a predetermined threshold value. On the other hand, an edge included in the image is extracted from the photographic image, and the extracted edge is superimposed and displayed on the image reproduced from the binarized parameter and the parameter representing the hue. As a result, the selected photographic image is displayed as an illustration.
[0010]
In such image processing, a photographic image is an image expressed by RGB, and an image expressed by parameters with independent brightness and hue can be an image by YCrCb. Both expressions are frequently used in the field of image processing, and tools for handling them are widely available. Therefore, if the above format is used, other image processing accompanying illustration can be easily performed.
[0011]
Illustration is greatly influenced by the magnitude of the threshold when binarizing the parameters representing brightness. When the parameter representing the brightness is expressed by 8 bits, the threshold value for binarization is desirably a value between 60 and 80 by default. Making the default threshold value around 72 and making this threshold value changeable within the range of 40 to 110 is also useful for adjusting the illustration atmosphere within a range that does not give a sense of incongruity as an illustration.
[0012]
When the extracted edge is superimposed on the image reproduced by the parameter after the brightness is binarized, an image of a part corresponding to the extracted edge can be displayed in a color indicating an outline. . The contour line is usually expressed in a specific color such as black, and the atmosphere of the illustration can be expressed more by superimposing it on the image.
[0013]
A configuration that can change the brightness and / or saturation of an image displayed as an illustration within a predetermined range is also useful. A slide bar or the like that adjusts the brightness or saturation is displayed on the screen, and by correcting the slide bar, the parameter representing the image may be changed.
[0014]
Furthermore, the second image processing apparatus of the present invention provides:
An image processing apparatus that outputs a result of a series of processing performed on a photographic image captured by a digital camera,
Image input means for inputting at least one of photographic images taken by the digital camera;
Binarization means for representing the input photographic image by a parameter whose brightness and hue are independent, and binarizing the parameter representing the brightness with a predetermined threshold;
Edge extraction means for extracting edges contained in the image from the photographic image;
Illustrating means for displaying the image as an illustration by displaying the extracted edge superimposed on the image reproduced from the binarized parameter and the parameter representing the hue;
Image arrangement arrangement means for arranging at least a part of the illustrated image in a predetermined area together with other images and characters constituting the image;
Output means for outputting the arranged images and characters to a printer capable of forming a multicolor image;
The main point is that
[0015]
In such an image processing apparatus, as in the first image processing apparatus, a process for making an illustration of a photographic image is performed. In particular, at least a part of an image captured by a digital camera is used to configure other images. Images, characters, and the like can be arranged, and the arranged images can be output to a printer to form a multicolor image. Therefore, it is possible to output an image that is illustrated based on an image taken by a digital camera in the form of a New Year's card, a card, a work, a stationery, or the like.
[0016]
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of the present invention will be described. FIG. 1 is an explanatory diagram showing a computer 20 as an image processing apparatus in which the image processing method of the present invention is implemented and a printer 30 connected to the computer 20. A card reader / writer 40 for reading and writing the memory card MC is connected to the computer 20. An image captured by the digital camera 50 is written in a memory card MC built in the digital camera 50. The memory card MC is removed from the digital camera 50 and mounted on the card reader / writer 40, whereby the image is captured by the digital camera 50. The processed image can be handled by the computer 20.
[0017]
The computer 20 is a well-known computer, and incorporates a CPU, ROM, RAM, a video signal output circuit, an interface with the card reader / writer 40, a hard disk and its control circuit. Description of these circuits is omitted. FIG. 2 is a block diagram illustrating functions related to image processing realized in the computer 20. Such functional blocks are actually realized by executing a predetermined program loaded from a hard disk built in the computer 20.
[0018]
As shown in FIG. 2, the computer 20 functioning as an image processing apparatus has an image data reading unit 100 that realizes a function of selecting and reading image data from a memory card MC attached to the card reader / writer 40, and image data reading. A conversion unit 110 that converts an expression format of data read from the unit 100 from RGB (each 8 bits) to YCrCb (each 8 bits), and a threshold value that predetermines a Y value that is a parameter representing brightness in the converted image data A binarization execution unit 120 that performs binarization by comparing with Yr, an image reproduction unit 130 that reproduces an image from the parameters after binarization of brightness, and noise in the read image data are removed. An edge extraction unit 140 that extracts an edge from the image to obtain a contour line, and overlays the contour line and the image reproduced by the image reproduction unit 130 Implementing the function unit such as an image forming unit 150 for forming an image, Te.
[0019]
Here, the image data reading unit 100 selects image data stored in the memory card MC and reads at least one of them. Specifically, the image data stored in the memory card MC in a format such as JPEG is displayed in a file format, and the user is allowed to select it. An example of the selection screen is shown in FIG. On this screen, a list of processes to be executed on the left side is shown in the form of a button. When the “select photo” button BL1 is operated, the image data existing in the memory card MC or the hard disk is displayed on the right side of the screen. Is displayed. The image data is displayed in the form of a file in the column CC1, and is displayed in the form of a thumbnail in the column CC2 below it. When a file name or thumbnail is selected in any of the columns CC1 and CC2 (for example, double-clicked with a mouse or the like), the selected image data is read from the memory card MC or the hard disk and displayed on the monitor 25 of the computer 20. Therefore, it is expanded in a display memory (not shown) in the computer 20 in the RGB (8 bits each) format. The developed image is displayed in the display column CC3 in FIG. The image PH read out in this way can be rotated 90 degrees to the left by the “left rotation” button BB bay at the top of the screen. Similarly, the “right rotation” button BB2 can rotate 90 degrees right. When the “pre-process” button BB3 is pressed, a pre-process defined in advance for the image PH, for example, a process of brightening the entire image when it is dark can be performed.
[0020]
The image data read out in this manner is converted in its expression format by the conversion unit 110 inside the computer 20. In the embodiment, the conversion unit 110 converts RGB format image data into a YCrCb format in which brightness and hue are independent parameters. This conversion can be easily realized by a known matrix operation.
[0021]
The binarization execution unit 120 sequentially reads image data expressed in the YCrCb format from the image origin (for example, the upper left corner) and performs binarization. Although details of this processing will be described later, roughly speaking, the Y value of the image data converted by the conversion unit 110 is compared with the threshold value Yr, and if it is larger than the threshold value Yr, it is set as a preset upper limit value (Ymax). If it is smaller than the threshold value Yr, the lower limit value (Ymin) set in advance is set. If the threshold value Yr is set to a small value, the image becomes whitish and the shadow range becomes narrow. If the threshold value Yr is set to a large value, the image becomes blackish and the shadow range becomes wide. The binarization execution unit 120 is attached with a threshold setting unit 125, and the threshold Yr used for binarization can be changed. In this example, the default value of the threshold Yr is 72 and can be varied between the minimum value 48 and the maximum value 108. In addition, after binarization about the brightness Y, it describes with the brightness Yh. The image reproduction unit 130 inversely converts the image data (YhCrCb) after binarization with respect to the image data (YCrCb) into the RGB format, and displays this on the monitor 25.
[0022]
In addition to the lightness binarization process described above, another edge extraction process is performed on the image stored and selected in the memory card MC. That is, the edge extraction unit 140 first removes noise included in the image data, and extracts an edge included in the data after removing the noise. In the extraction of the edge, the image data of the original image is used as it is for the pixel determined not to be an edge, and when it is determined to be an edge, the data of the pixel is set to black. As a result, the pixel determined to be an edge is set to black, and is treated as a contour line in the subsequent processing. The noise removal and edge extraction methods will be described later in detail. The edge extraction unit 140 is attached with a designation unit 145 for performing various designations. The designation unit 145 can designate the degree of noise removal at the time of noise removal and designate the number of contour lines.
[0023]
The image forming unit 150 superimposes the image in which the contour line is formed by the edge extraction in this way and the binarized image reproduced in advance. The image forming unit 150 compares the output of the image reproduction unit 130 and the output of the edge extraction unit 140, sets the pixel to black if it corresponds to the contour, and reproduces the image if it does not correspond to the contour. The image data of the unit 130 is adopted as the pixel data.
[0024]
As described briefly above, in this image processing apparatus, binarization of brightness and extraction of edges are performed from original image data, and a processed image is formed from both. By performing such processing, it is possible to obtain an illustrated image from a photographic image. When the “illustration” button BL2 on the left side is clicked on the screen shown in FIG. 3, the above illustration processing is performed, and the illustrated image is displayed in the column CL1, as shown in FIG. The Since these processes are uniformly performed using a preset threshold value Yr and the like, assuming that the obtained image is not a desired one, the already described threshold setting unit 125, the specifying unit 145, etc. are attached. Yes. Similarly, a setting change unit 155 that changes the setting of the image forming unit 150 is also provided. As shown in FIG. 4, the threshold setting unit 125, the specifying unit 145, or the setting changing unit 155 actually has five slide bars SL1 displayed next to the column CL3 displaying the illustrated image. Or SL5.
[0025]
The upper three slide bars SL1 to SL3 relate to the adjustment of the color of the illustrated image, and the uppermost slide bar SL1 corresponds to the threshold setting unit 125 for setting a shadow range. By moving the slider of the slide bar SL1, it is possible to adjust the range of the shadow (the black portion in the illustrated image). Moving the slider toward “narrow” reduces the black area, and moving it toward the “wide” area increases the black area. This slider movement is also reflected in the image of the column CL1 immediately, as is the case with the other slide bars SL2 to SL5. The second slide bar SL2 is for setting the brightness of the illustrated image, and the third slide bar SL3 is for setting the vividness (saturation) of the illustrated image. These correspond to the setting change unit 155.
[0026]
The lower two slide bars SL4 and SL5 relate to the adjustment of the contour line and noise, and correspond to the designation unit 145. The slide bar SL4 sets the number of contour lines. When the slider is moved to the “less” side, the number of contour lines in the illustration decreases. On the other hand, moving the slider to the “large” side increases the number of contour lines in the illustration. The slide bar SL5 sets the strength of noise removal, and adjusts the amount of fine black dots (noise) remaining in the illustrated image.
[0027]
Next, details of processing in the binarization execution unit 120 and the like will be described. FIG. 5 is a flowchart showing an outline of binarization processing. As shown in the figure, the binarization execution unit 120 that performs binarization processing first sets a threshold value Yr (step S200). The threshold Yr sets a shadow range as image processing, and corresponds to operating the slider of the slide bar SL1 shown in FIG. 4 from the user side. In this example, the default value of Yr is 72, the minimum value (narrow) is 48, and the maximum value (wide) is 108.
[0028]
After setting the threshold value Yr, the image data of each pixel is sequentially read from the origin for the photographic image (step S210). Next, it is determined whether or not the Y value of the pixel is larger than the set threshold value Yr (step S220). If the Y value is larger than the threshold value Yr, the Y value is set to the upper limit value Ymax (value 255 in this embodiment). (Step S230) If the threshold value Yr or less, the Y value is set to the lower limit value Ymin (value 0 in this embodiment) (Step S240). The Y value after setting is represented as Yh.
[0029]
After the above processing, it is determined whether the processing has been completed for all the pixels (step S250). If the processing has not been completed, the pixel of interest is advanced by one (step S260), and the processing from step S210 to step S210 has been described above. Repeat the process. When the processing for all the pixels is completed, the obtained image data (YhCrCb) is converted into RGB format data for display (step S270), and then the process goes to “END” to end the processing. . As a result of the above processing, image data (YhCrCb) obtained by binarizing only the brightness Y with respect to the original image data is obtained.
[0030]
FIG. 6 is a flowchart showing a process for changing the brightness of an image by the slide bar SL2. In this process, the brightness correction value C set by the slide bar SL2 is read (step S300), and the binarized Yh value is corrected by the correction amount C using this correction value. It is. The correction amount C can take a value of −32 to +32, and is −32 if the slider is set to the “dark” side, and +32 if the slider is set to “bright”. Using this correction amount C, a process of correcting the image data (YhCrCb) of all the pixels is performed (step S310), and the process ends. Note that the processing shown in this flowchart is actually executed only when the slider of the slide bar SL2 is moved. When the correction amount C is 0, the original image is not corrected.
[0031]
Next, the saturation changing process will be described. The saturation of the illustrated image is corrected by moving the slider of the slide bar SL3 shown in FIG. This process is performed on the image data (RGB) after being converted into RGB data by the binarization process. The saturation correction process is shown in the flowchart of FIG. When the slider of the saturation correction slide bar SL3 is changed, the processing shown in FIG. 7 is started, and first, the saturation correction value k is read (step S350). Next, the original image data (RGB) is once converted into the HSV (hue, saturation, brightness) format (step S360), and the saturation value S is multiplied by a coefficient k (step S370). . In the embodiment, the range of the coefficient k set by the slide bar SL3 is 0.25 to 4.0. After such saturation correction is performed for all the pixels, this time, the image data in the HSV format is inversely converted into the RGB format (step S380), and the process is terminated. Similar to the brightness correction, the saturation correction is performed immediately each time the slider of the slide bar SL3 is moved, and the saturation of the image displayed in the display field CL1 is changed.
[0032]
Next, an edge extraction process performed by the edge extraction unit 140 and a change in the number of contour lines adjusted in response to the designation by the designation unit 145 will be described. This process is performed according to the flowchart shown in FIG. When this process is started, the threshold value B is first set by the designation unit 145 (step S400). Actually, this designation is performed by the slide bar SL4 shown in FIG. The determination as to whether or not the edge is an edge is made by determining that an edge is where the difference between the color of the pixel of interest and the average color of surrounding pixels is equal to or greater than a threshold value B. In the present embodiment, the threshold B for this is a value of 2 for the default, a value of 0 for the minimum, and a value of 4 for the maximum. That is, when the slider of the slide bar SL4 shown in FIG. 4 is brought to the “less” side, the threshold value B is set to the value 4 side, and when it is brought to the “more” side, the threshold value B is a value. Set to 0 side. Note that in an image represented by 8-bit image data for each color, the difference between the image data of the pixel of interest and the average value of surrounding pixels can theoretically take from 0 to 255, but a photograph or the like In such a natural image, an edge is not formed only by such a large change in data, and if a threshold value is set in a range of about 0 to 4, an illustration can be achieved.
[0033]
Next, a process of reading the image data S of the pixel P of interest is performed (step S410). At this time, the image data is read out in the RGB format. Next, a process of calculating an average value Sav of image data (color) of 8 pixels around the pixel of interest is performed (step S420). Actually, the average value Sav is obtained for each color of RGB. Subsequently, it is determined whether or not the difference between the image data S of the pixel P of interest and the average value Sav is greater than or equal to the threshold value B (step S430). This determination may be made as | S−Sav |> B when all the colors of RGB are equal to or greater than the threshold value B, or may be determined by an average value of differences for RGB.
[0034]
If it is determined that the difference between the image data S of the pixel P of interest and the average value Sav of the image data of the eight neighboring pixels is greater than or equal to the threshold B, that pixel is opposed to an edge (step S440). If it is determined as an edge, the image data at that point is set to black. If the determination in step S430 does not hold, it is determined that the background is not an edge, and the image data of the pixel is held as it is. The above processing relates to one focused pixel, but in practice, it is performed for all the pixels of the image data binarized by the binarization execution unit 120 and returned to the RGB format.
[0035]
When the above processing is executed, it is determined that the pixel in which the pixel of interest has changed by more than the threshold value B as seen from the average image data of the surrounding eight pixels is an edge, and is used as an outline. Processing to change to a black dot is executed. Judgment as to whether or not an edge is based not only on lightness but also on a color-by-color basis using image data in RGB format, the points where the hue changes even if the brightness is the same are extracted as edges Is done. If the threshold value B is small, even a portion with a small change is picked up as a contour line, so the number of contour lines increases.
[0036]
Next, the noise removal process performed simultaneously with the contour line extraction process will be described. Noise removal corresponds to a process of removing isolated points from the edges extracted as contour lines. An outline of this processing is shown in FIG. As shown in the figure, when this process is started, first, a process of setting the threshold value Tp specified by the specifying unit 145 to the threshold value T for noise removal is performed (step S500). The threshold value Tp is actually designated by the slide bar SL5 shown in FIG. As the slider of the slide bar SL5 is moved to the left, noise removal becomes weaker, that is, the number of isolated contour lines that look like noise increases, and as the slider is moved to the right, noise removal becomes stronger, that is, contour. The number of lines generally increases. Since the threshold value Tp for setting the noise removal strength is specified by 8-bit data, the value 0 to 255 can be theoretically specified internally. However, in this embodiment, the threshold value Tp is 16 by default. The value can be set to 0 (no noise removal) and up to 56.
[0037]
After setting the threshold value T, the image data S of the pixel of interest Pmn is read and processed (step S510). Since the position of the pixel of interest P can be specified using two-dimensional coordinates (m, n), the coordinates in the X direction are represented by m and the coordinates in the Y direction are represented by n. Next, the variable N is initialized to the value 1 and the image data calculation variable L is initialized to the value 0 (step S520), and one of the 8 neighboring pixels of the pixel Pmn is compared with the image data (color unit). Processing for obtaining the difference ΔS is performed (step S530). The variable N is used to designate neighboring pixels. Next, it is determined whether or not the difference ΔS of the image data is equal to or smaller than the previously set threshold value T (step S540). Here, if the difference ΔS is equal to or smaller than the threshold value T, a process of adding the image data of the pixel itself to the image data L of the pixel of interest Pmn is performed (steps S4 to 550). If the difference ΔS is larger than the threshold value T, nothing is added to the calculation variable L.
[0038]
Next, the variable N is incremented by 1 (step S560), and it is determined whether or not the variable N is greater than 8 (step S570). If the variable N is not greater than the value 8 (if the value is 8 or less), it is determined that comparison with all the pixels around the pixel of interest Pmn has not been completed, the process returns to step S530 and the above process is repeated. On the other hand, if all the comparisons with the surrounding eight pixels have been completed, the process proceeds to step S480, where the calculation data L accumulated for the pixel of interest is multiplied by 8, and data for that pixel is obtained. Processing is performed (step S580). This process is actually performed after the already described outline extraction process. That is, if a pixel extracted as a contour line is adjacent to a pixel extracted as a contour line in several directions (ΔS ≦ T), the image data S of the pixel is held at a high value ( In step S580), if there is no contour line in the adjacent position or there are few contour lines, the image data of the pixel is corrected to a small value and erased as noise.
[0039]
According to the present embodiment described above, an illustration-like image can be obtained from a photographic image by performing illustration processing very easily. In particular, in this embodiment, the image data is once converted into a format of image data in which the brightness and hue are separated as parameters, and the parameter Y representing the brightness is compared with a predetermined threshold Yr. An appropriately illustrated image can be obtained by a very simple method. The default value 72 for the threshold value Yr (when an image is expressed by 8 bits) is a value that has been found through trial and error, and is a threshold value that can appropriately illustrate many photographic images. In addition, while displaying the image once illustrated in the column CL1, using the slide bars SL1 to SL5, the shadow portion size, brightness correction, vividness correction, contour line depth and noise removal strength are enhanced. It is very easy to change the size. In addition, the results of those changes are immediately reflected in the image displayed in the column CL1, and the results of the image processing can be confirmed.
[0040]
When it is determined that the image displayed in the column CL1 is appropriate, the “save” button BL3 shown in FIG. 4 can be operated to save the image after the illustration. Moreover, it is good also as what adds a character, clip art, etc. to the illustrated image, adjusts to a desired image, and prints this as a New Year's card, a card, a calendar, etc.
[0041]
As mentioned above, although embodiment of this invention was described, this invention is not limited to such embodiment at all, and in the range which does not deviate from the summary of this invention, it can implement with a various form. Of course. For example, the image processing apparatus of the present embodiment can also be embodied as an image processing method, a recording medium on which the image processing method is recorded, and a program that realizes the image processing method. Further, various filters may be prepared for the illustrated image, and for example, the once illustrated image may be modified again in a watercolor style, or may be added with a process such as arranging in an OO painter style. It is also possible to incorporate this image processing into a specific application such as New Year's card creation software.
[Brief description of the drawings]
FIG. 1 is an explanatory diagram illustrating a schematic configuration of an image processing apparatus according to an embodiment.
FIG. 2 is a block diagram illustrating a functional configuration of the image processing apparatus.
FIG. 3 is an explanatory diagram showing how an image is selected.
FIG. 4 is an explanatory diagram showing how various settings are made for an illustrated image.
FIG. 5 is a flowchart showing a binarization processing routine;
FIG. 6 is a flowchart showing a brightness change processing routine;
FIG. 7 is a flowchart showing a processing routine for changing saturation.
FIG. 8 is a flowchart showing a contour processing routine for extracting a contour line;
FIG. 9 is a flowchart showing a noise removal processing routine;
[Explanation of symbols]
20 ... Computer
25 ... Monitor
30 ... Printer
40: Card reader / writer
50 ... Digital camera
100: Image data reading unit
110: Conversion unit
120... Binarization execution unit
125: Threshold setting unit
130: Image reproduction unit
140. Edge extraction unit
145 ... Designation part
150: Image forming unit
155 ... Setting change section

Claims (10)

An image processing method for inputting and processing a photographic image,
Select at least one of the photographic images recorded on the recording medium,
The selected photographic image is represented by parameters whose brightness and hue are independent,
The parameter representing the brightness is binarized by comparing with a predetermined threshold value,
Extracting the edge contained in the image from the photographic image,
An image processing method for displaying the image as an illustration by superimposing the extracted edge on an image reproduced from the binarized parameter and the parameter representing the hue. The image processing method according to claim 1,
The photographic image is an image expressed in RGB,
The image processing method, wherein the image in which the brightness and the hue are expressed by independent parameters is an image by YCrCb. The image processing method according to claim 1,
The parameter is expressed in 8 bits;
The threshold value for binarization is an image processing method having a value between 60 and 80 by default. The image processing method according to claim 3,
The default threshold value is a value around 72, and the threshold value can be changed within a range of 40 to 110.   The image processing method according to claim 1, wherein when the edge is extracted, an image of a part corresponding to the edge is displayed in a color indicating an outline.   The image processing method according to claim 1, wherein the brightness and / or saturation of the image displayed as an illustration is changed within a predetermined range. An image processing apparatus for inputting and processing a photographic image,
Image selection means for selecting at least one of the photographic images recorded on the recording medium;
Binarizing means for representing the selected photographic image by a parameter whose brightness and hue are independent, and binarizing the parameter representing the brightness with a predetermined threshold;
Edge extraction means for extracting edges contained in the image from the photographic image;
An image provided with an illustration means for displaying the extracted image by displaying the extracted edge on the image reproduced from the binarized parameter and the parameter representing the hue. Processing equipment. A program that is read by a computer and performs image processing on a photographic image by the computer,
A function for selecting at least one of photographic images recorded on a recording medium;
A function of expressing the selected photographic image by a parameter whose brightness and hue are independent, and binarizing the parameter representing the brightness with a predetermined threshold;
A function of extracting an edge included in the image from the photographic image;
A computer that realizes, by a computer, a function of displaying the image as an illustration by superimposing the extracted edge on an image reproduced from the binarized parameter and the parameter representing the hue.   A recording medium on which the program according to claim 8 is recorded. An image processing apparatus that outputs a result of a series of processing performed on a photographic image captured by a digital camera,
Image input means for inputting at least one of photographic images taken by the digital camera;
Binarization means for representing the input photographic image by a parameter whose brightness and hue are independent, and binarizing the parameter representing the brightness with a predetermined threshold;
Edge extraction means for extracting edges contained in the image from the photographic image;
Illustrating means for displaying the image as an illustration by displaying the extracted edge superimposed on the image reproduced from the binarized parameter and the parameter representing the hue;
Image arrangement arrangement means for arranging at least a part of the illustrated image in a predetermined area together with other images and characters constituting the image;
An image processing apparatus comprising output means for outputting the arranged images and characters to a printer capable of forming a multicolor image.

Images