JP2024034772A - Image processing apparatus, image processing method, and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To make it possible to give a preview useful to a user when giving the preview based on accumulated images.

SOLUTION: An image processing apparatus accumulates images created from print data through processing performed by a raster image processor and attributes of objects and commands acquired on the basis of the print data, performs image processing on the accumulated images, and creates and displays a preview image on the basis of the accumulated images. When the commands indicate execution of predetermined image processing, the image processing apparatus creates a preview image obtained by defining an area corresponding to an object of a first attribute in the accumulated images as a first image in a specific color.

SELECTED DRAWING: Figure 2

COPYRIGHT: (C)2024,JPO&INPIT

Description

The present invention relates to an image processing technique for generating preview images.

Printers are often equipped with a memory that can store images. For example, when printing an image, if the printer driver gives an instruction to store the image, the image can be stored in the internal memory. can. Further, a printer having a scanning function can store the scanned image in the memory if an instruction to store the scanned image is given via a UI (user interface), for example. The printer can perform various processing on the accumulated images, such as printing them or transmitting them to a personal computer (PC).

Further, Patent Document 1 discloses a technology that allows a user to check an image by displaying an image stored in a memory as a preview image in a printer.

Japanese Patent Application Publication No. 2006-238106

Incidentally, the images stored in the memory of the printer are images before being subjected to image processing in the printer (hereinafter referred to as printer image processing). This is because memory cost reduction and output image optimization are taken into consideration. Taking dithering processing as an example of printer image processing, for example, an image that was 600 dpi becomes 2400 dpi through dithering processing that matches the resolution of the output engine, and a large memory capacity is required to store that image. Become. For example, when an image after printer image processing is stored, an image with gradation matching the engine state at the time of image storage will be generated and stored; It may not be an image. For these reasons, the image stored in the memory of the printer is the image before printer image processing is performed.

On the other hand, the image stored in the printer's memory is an image before printer image processing is performed as described above, so even if a preview image is generated from that image, it may not be an accurate preview of the printer output image. Sometimes it doesn't happen. For example, printer image processing may be performed on only a portion of an image and the image is stored in memory, but since that image has only had printer image processing performed on a portion of it, previewing it as it is may give the user a sense of discomfort. I'll give it away. In this way, previews using images stored in memory may not be useful to the user.

Therefore, an object of the present invention is to enable a preview that is useful for the user when performing a preview based on accumulated images.

The image processing apparatus of the present invention includes a storage means for storing an image generated from print data through processing by a raster image processor, and object attributes and commands acquired based on the print data; a processing means for performing image processing on an image; a generation means for generating a preview image based on the accumulated images; and a preview means for displaying the preview image; , the generating means generates the preview image in which a region corresponding to the object of the first attribute among the accumulated images is set as the first image in a specific color. Features.

According to the present invention, when performing a preview based on accumulated images, it is possible to perform a preview that is useful for the user.

FIG. 1 is a block diagram showing the configuration of an image processing system. FIG. 2 is a functional block diagram showing each functional unit of a host PC and an image forming apparatus. FIG. 3 is a diagram showing an example of a drawing command. FIG. 3 is a diagram illustrating an example of an input image and an image after discriminability improvement processing. It is a flow chart of discriminability improvement processing of a 1st embodiment. FIG. 3 is a diagram used to explain filter processing. FIG. 3 is a diagram used to explain trapping processing. 3 is a flowchart of processing from print data acquisition to preview. It is a flowchart of preview image generation processing. It is a figure showing an example of a preview screen. 12 is a flowchart of discriminability improvement processing according to the second embodiment. FIG. 3 is a diagram showing an example of a color value list.

Embodiments according to the present invention will be described below with reference to the drawings. The following embodiments do not limit the present invention, and not all combinations of features described in the present embodiments are essential to the solution of the present invention. The configuration of the embodiment may be modified or changed as appropriate depending on the specifications and various conditions (conditions of use, environment of use, etc.) of the device to which the present invention is applied. Moreover, a part of each embodiment described later may be combined as appropriate. In each of the following embodiments, the same configurations will be described with the same reference numerals.

<First embodiment>
FIG. 1 is a diagram showing an example of the configuration of an image processing system 117 according to the first embodiment. The image processing system 117 of this embodiment includes an image forming apparatus 101 and a host PC 119.

The host PC 119 is configured to include a CPU 120, ROM 121, RAM 122, HDD 123, etc., like a general personal computer. The host PC 119 generates print data based on electronic data such as document documents and presentation documents, and outputs the print data to the image forming apparatus 101 .
Further, the image processing system 117 may include a PC 127. The PC 127 is, for example, an external PC, and is assumed to be a server or cloud that performs various image processing.

The image forming apparatus 101 is an example of an image processing apparatus according to the present embodiment, and is a multi-function peripheral (MFP) that integrates multiple functions such as a printer function and a scan function. Image forming apparatus 101 includes a control section 110, an operation section 118, an image output section 109, an image reading section 108, a display section 125, and an image transmission section 126.

The operation unit 118 includes a touch panel, various switches, buttons, etc., and acquires user operations on these and outputs them to the control unit 110.
The image output unit 109 is a printer unit that performs printing on a print medium.
The image reading unit 108 is, for example, a scanner, and reads images and the like.
The display unit 125 is a display device having a display, and in this embodiment displays a UI (user interface) screen including a preview image as described later.
The image transmitting unit 126 transmits, for example, an image read by the image reading unit 108 to the host PC 119, PC 127, etc.

The control unit 110 centrally controls the image forming apparatus 101 and performs various processes including image processing for improving discrimination and image processing for generating a preview image according to the present embodiment, which will be described later. The control unit 110 includes a CPU 105, a ROM 106, a RAM 107, an auxiliary storage device 111, an operation unit I/F 112, a printer I/F 113, a scanner I/F 114, a network I/F 115, a display I/F 124, and the like.

The CPU 105 controls the operation of the image forming apparatus 101 by loading a program stored in the ROM 106 into the RAM 107 and executing it, and also performs various processes including image processing according to the present embodiment described later. The RAM 107 is a temporary storage memory, and is used as a memory in which a program read from the ROM 106 is expanded and a memory in which image data and the like are temporarily stored. The ROM 106 stores an OS (operating system) of the image forming apparatus 101, various control programs and parameters, and various applications including an application program (hereinafter referred to as an application) that implements the image processing of this embodiment. The CPU 105 controls the image forming apparatus 101 by loading a control program stored in the ROM 106 into the RAM 107 and executing it. Control by the CPU 105 includes control of a print function by the image output unit 109, control of a scan function by the image reading unit 108, and the like. Further, the control by the CPU 105 includes control for recording, in the auxiliary storage device 111, images read by the image reading unit 108, images used for printing by the image output unit 109, and the like. Furthermore, the control of the CPU 105 includes control for transmitting stored images in the auxiliary storage device 111 from the image transmitting unit 126 to the host PC 119 via the network I/F 115, and control for receiving images sent from the host PC 119 via the LAN 116. Also included. The auxiliary storage device 111 includes, for example, an HDD (hard disk drive), an SDD (solid state drive), or other nonvolatile memory. The auxiliary storage device 111 and RAM 107 are also used to temporarily spool images and data.

The CPU 105 also performs processing such as generating a preview image as described later based on the image stored in the auxiliary storage device 111 and sending it to the display unit 125 via the display I/F 124 for previewing. Details of the preview image generation process in this embodiment will be described later. In addition, the CPU 105 also controls the operation unit 118 via the operation unit I/F 112.

FIG. 2 is a functional block diagram showing main functional units related to this embodiment in the host PC 119 of the image processing system 117 and the image forming apparatus 101.
<Print processing>
First, the general flow of print processing in the image processing system 117 will be explained with reference to FIG.

The application 201 of the host PC 119 creates electronic data such as documents and presentation documents. The printer driver 202 is a driver that generates print data from electronic data created by the application 201 and sends the print data to the image forming apparatus 101 for printing. It is assumed that the print data generated by the printer driver 202 is, for example, PDL (Page Description Language) data. PDL is a language information that allows image information to be transferred to a printer using a small amount of data by dividing drawing data on a page into drawing elements called objects, such as characters, figures, and images, and converting them into object codes. be. The printer driver 202 also creates commands for controlling the operation of the image forming apparatus 101 and includes them in the print data (PDL data). The print data created by the printer driver 202 is then sent to the image forming apparatus 101. The application 201 and printer driver 202 are realized by the CPU 120 loading programs stored in the ROM 121 into the RAM 122 and executing them.

Upon receiving print data from the host PC 119, the command processing unit 102 of the image forming apparatus 101 analyzes the command and generates a raster image based on the print data. First, the command determining unit 203 in the command processing unit 102 determines the type of PDL from print data. PDL types include PostScript: PS (PostScript is a registered trademark), Printer Command Language (PCL), and the like.

Next, the command analysis unit 204 extracts and analyzes the PDL type command specified by the command discrimination unit 203.
Next, the conversion adjustment unit 205 executes processing according to the command analysis result by the command analysis unit 204. For example, the conversion adjustment unit 205 performs color conversion processing, adjustment processing of the thickness of lines, objects, etc., on information such as objects.
The command execution unit 206 executes raster image processor (RIP) processing according to the command analysis result of the command analysis unit 204 and the processing result of the conversion adjustment unit 205. By executing this RIP process, a raster image and attribute information describing the attributes of each object included in the raster image are generated.
Then, the storage control unit 103 stores the command analysis result by the command analysis unit 204 and the raster image and attribute information generated by the command execution unit 206 in a recording area in the auxiliary storage device 111.

The image processing unit 104 performs various image processing using the raster image and attribute information generated by the command execution unit 206 or the raster image and attribute information stored in the auxiliary storage device 111. For example, the color conversion processing unit 211 of the image processing unit 104 performs color conversion from an RGB color space to a CMYK color space, color conversion from color to monochrome, or color conversion from an RGB color space to another RGB color space. conduct. The filter processing unit 212 performs sharpness processing such as edge enhancement and smoothing. The trapping processing unit 213 performs trapping processing in which the color planes sneak into adjacent pixels in order to prevent white spots due to misalignment between the color planes. The gamma processing unit 214 performs gamma processing using a one-dimensional LUT (lookup table) according to the characteristics of the printer. In addition, the image processing unit 104 also performs dithering processing on the gamma-processed image.

Furthermore, in the case of the present embodiment, the image processing unit 104 performs predetermined image processing (hereinafter referred to as discriminability improvement processing) for improving discriminability as described later based on the raster images accumulated in the auxiliary storage device 111. It also performs image processing to generate preview images. Although details will be described later, the discriminability improvement process is realized by the filter processing section 212 or the trapping processing section 213. The image processing for generating the preview image will also be described in detail later.

The preview control unit 225 performs control to preview, on the display unit 125, a preview image generated by the image processing unit 104 as described later based on the raster image and attribute information stored in the auxiliary storage device 111. The transmission control unit 226 performs control for transmitting the raster images stored in the auxiliary storage device 111 from the image transmission unit 126 to the outside.

Note that each functional unit from the command processing unit 102 to the image processing unit 104 of the image forming apparatus 101 is realized by the CPU 105 executing the program according to the present embodiment, but some or all of them may be It may be realized by a hardware configuration such as a circuit.

Next, details of the processing performed by the command processing unit 102 in FIG. 2 will be explained using FIG. 3. FIG. 3 is a diagram used to explain an example in which the command analysis unit 204 in FIG. 2 analyzes a command, and the command execution unit 206 executes RIP processing to generate a raster image. FIG. 3(a) is a diagram showing an example of the description content of the drawing command 300, and FIG. 3(b) is a diagram showing an example of a raster image generated based on the drawing command 300 of FIG. 3(a). It is. The following describes the flow in which the command analysis unit 204 analyzes a command written in PDL, and the command execution unit 206 executes RIP processing to generate a raster image according to the analysis result by the command analysis unit 204. .

Here, commands include drawing commands and control commands.
The drawing commands include a color mode setting command, a color setting command, an object drawing command, a character size setting command, a font setting command, a character drawing command, a coordinate setting command, a line thickness setting command, an image drawing command, and the like. The color mode setting command is a command for setting the color mode of print data, and the color setting command is a command for setting colors. Object drawing commands are commands for drawing objects such as graphics, characters, and images. The character size setting command is a command to set the size of characters, the font setting command is a command to set the font of characters, and the character drawing command is a command to draw characters. The coordinate setting command is a command for setting coordinates, the line thickness setting command is a command for setting line thickness, and the image drawing command is a command for drawing an image. The configuration of a series of these drawing commands is similar regardless of the type of object.

The control commands include a finishing information designation command, a conversion designation command, an accumulation designation command, a discriminability improvement process designation command, and the like. The finishing information designation command is a command that designates finishing information for print data, such as paper size designation such as A4 or A3, so-called 2-in-1 setting to fit two pages on one output paper, and designation to print on both sides. The conversion designation command is a designation command for converting print data into monochrome or the like, and the storage designation command is a command for designating whether or not to store images in the auxiliary storage device 111. The discriminability improvement process designation command is a command that specifies execution of a discriminability improvement process, which will be described later.

The contents of the drawing command 300 shown in FIG. 3(a) will be explained. Note that the subsequent drawing commands 300 and color values are based on an 8-bit image.
The third “Set Color (255, 128, 128)” of the drawing commands 300 is a color setting command, and indicates setting red with RGB values of R=255, G=128, and B=128. The fourth "Draw Box (coordinates (X1, Y1), coordinates (X2, Y2) fill)" is an object drawing command that draws a rectangular object from coordinates (X1, Y1) to coordinates (X2, Y2). It shows that. That is, the third color setting command and the fourth object drawing command indicate that a rectangular red object is to be drawn. Similarly, the fifth color setting command "Set Color (153, 153, 255)" indicates that blue with RGB values of R=153, G=153, and B=255 is set. The sixth object drawing command, Draw Box (coordinates (X2, Y1), coordinates (X3, Y2) fill), draws a rectangular object from coordinates (X2, Y1) to coordinates (X3, Y2). It is shown that. That is, the fifth color setting command and the sixth object drawing command indicate that a rectangular blue object is to be drawn.

Then, in response to the analysis of the drawing command 300 by the command analysis unit 204, the command execution unit 206 executes RIP processing, thereby generating raster images 301 and 302 as shown in FIG. 3(b). That is, in FIG. 3(b), a raster image 301 is an image drawn by the third and fourth commands in the drawing command 300 shown in FIG. 3(a) and subjected to RIP, and becomes a red rectangular image. . Similarly, the raster image 302 is an image drawn by the fifth and sixth commands in the drawing command 300 and subjected to RIP processing, and becomes a blue rectangular image.

<Processing to improve discrimination when converting from color to monochrome>
Next, in this embodiment, a process for improving discriminability when converting from color to monochrome will be described, taking as an example a case where a color image is converted to monochrome (gray conversion) and output.
Here, when a color image is converted to monochrome (gray conversion), hue and saturation information is lost, so objects of different colors in the color image may become indistinguishable, or difficult to distinguish.

FIG. 4A is a diagram showing an example of an input image 401. It is assumed that the input image 401 illustrated in FIG. 4A includes adjacent objects such as a graphic 402 and characters 403, and an image 404 such as a photograph that is an object other than graphics or characters. That is, in the example of the input image 401, it is assumed that the filled rectangular object is a graphic 402, and that the graphic 402 includes an object of the alphanumeric character "0" 503. Further, it is assumed that the graphic 402 is red with an RGB value of (255, 128, 128), for example, and the character 403 is blue with an RGB value of (153, 153, 255), for example. On the other hand, it is assumed that a square object filled with dots is an image 404 such as a photograph.

If it is assumed that the input image 401 shown in FIG. 4(a) is converted into monochrome by general NTSC conversion, for example, the RGB values are weighted and converted into monochrome as shown in the conversion formula below. The following processing will be performed. That is, the graphic 402 has a gray value of 0.299×255+0.587×128+0.114×128=166, and the character 403 has a gray value of 0.299×153+0.587×153+0.114×255=165. . In this case, the gray values of the adjacent graphic 402 and character 403 after monochrome conversion are 166 and 165, which are almost the same values, so the character 403 in the graphic 402 in particular becomes indistinguishable (indistinguishable). It ends up. Therefore, in the present embodiment, both of the graphic attribute and character attribute objects are treated as objects of the first attribute, and the discriminability improvement process described below is performed on adjacent objects of the first attribute. As a result, in this embodiment, it is possible to obtain an output that can be distinguished even if the gray values are substantially the same (in particular, the characters 403 can be distinguished). In other words, in the case of the input image 401 in FIG. 4A, the objects of the first attribute that are the target areas of the discriminability improvement processing described later are the graphic 402 and character 403 objects. On the other hand, for image objects such as photographs in the image, monochrome conversion is performed with emphasis on the gradation of the image, and the object is not subjected to the discrimination improvement process. Therefore, in this embodiment, an image object such as a photograph is treated as an object with a second attribute different from the first attribute.

In the image forming apparatus 101 of the first embodiment, when converting a color image into monochrome, an edge (border line) is added to the boundary between adjacent objects of the first attribute in the color image. This improves the distinguishability between characters and graphics after monochrome conversion. That is, in the case of this embodiment, the image forming apparatus 101 performs edge enhancement processing to add an edge to the boundary between adjacent objects of the first attribute as a discriminability improvement processing between the objects.

An image 405 in FIG. 4(b) shows the result of monochrome conversion in which the image forming apparatus 101 of the first embodiment performs discriminability improvement processing on the input image 401 illustrated in FIG. 4(a). There is. In the discriminability improvement processing according to this embodiment, by adding a dark (or thin) edge to the boundary between the graphic 402 and the character 403 in FIG. 4(a), the graphic 406 as shown in FIG. 4(b) becomes the character 407. That is, even if the graphic 402 and the characters 403 are converted to substantially the same gray value, they can be distinguished as the graphic 406 and the characters 407 shown in FIG. 4(b). Note that the image 404 in FIG. 4(a) is converted into an image 408 in FIG. 4(b) after monochrome conversion with emphasis on gradation.

Here, when a color image is converted to monochrome (gray conversion) and printed, etc., monochrome output is generally specified in the printer driver 202 on the host PC 119 side. Then, monochrome conversion is performed by the application 201 and printer driver 202 on the host PC 119 side, and the image stored on the image forming apparatus side also becomes a monochrome image.
In contrast, in the case of the present embodiment, in order to perform discriminability improvement processing in the image forming apparatus 101, even if monochrome output is specified by the printer driver 202 on the host PC 119 side, the image forming apparatus 101 does not output a color image. The print data shown is input. Further, at this time, the color mode designation command of the drawing command sent from the host PC 119 to the image forming apparatus 101 designates monochrome, and the conversion designation command of the control command designates monochrome conversion. Further, if it is specified that the image forming apparatus 101 is to store images, the storage designation command of the control command is set to indicate that the images are to be stored. Furthermore, if the image forming apparatus 101 is designated to perform the discriminability improvement process, the discriminability improvement process designation command of the control command is set to indicate that the discriminability improvement process is to be performed.

FIG. 5 is a flowchart showing the flow of discriminability improvement processing in the image forming apparatus 101 of the first embodiment. Note that in each flowchart that follows, each processing step (processing step) is represented by "S". Further, the processes in each of the subsequent flowcharts are performed by the corresponding functional units shown in FIG. 2 described above.

In S501, the command execution unit 206 executes RIP processing and generates a raster image and attribute information.
Next, in S502, the image processing unit 104 performs edge enhancement processing to add edges to the boundary portions between objects of the first attribute such as characters and graphics. The edge enhancement processing in S502 is realized by filter processing in the filter processing unit 212 or trapping processing in the trapping processing unit 213. Details of the filter processing by the filter processing section 212 or the trapping processing by the trapping processing section 213 will be described later. Note that since the image 404 shown in FIG. 4A is an object of the second attribute, it is not subject to edge enhancement processing. In other words, in the case of images such as photographs, edge enhancement processing is not performed.

Next, in S503, the image processing unit 104 converts the color raster image into monochrome. Conversion from color to monochrome is performed in the color conversion processing unit 211. Here, all objects including the object subjected to edge enhancement processing in S502 are converted to monochrome. For example, if the input image to the color conversion processing unit 211 is an image in RGB space, the color conversion processing unit 211 calculates a gray value by weighting each value of RGB, and then inverts the value. The value of K, which is the density signal value, is calculated. For example, if the input image of the color conversion processing unit 211 is an image in CMYK space, the color conversion processing unit 211 converts each CMYK value into a K signal value. Note that although only the discriminability improvement processing is described here, other necessary image processing is also executed as appropriate, and the image data after these image processing is transmitted to the image output unit 109.

As described above, in this embodiment, the image processing unit 104 performs edge enhancement processing to add edges to the boundary portions between objects of the first attribute, which would become indistinguishable if they were simply converted to monochrome. Converts a color image to monochrome (gray conversion). This allows these objects to be distinguished from each other.

Note that the edge enhancement processing in S502 is not limited to filter processing or trapping processing, but may be processing that applies a one-dimensional LUT that makes the output density signal value darker for each color version of RGB. Also, when applying trapping processing, in order to ensure edge enhancement between adjacent objects during trapping processing, it is necessary that adjacent objects do not have the same color plate, so adjust the color values in advance. Do it like this.

<Edge enhancement processing by filter processing unit>
Next, as an example of the edge enhancement processing performed in S502, an example in which filter processing by the filter processing unit 212 is applied will be described with reference to FIG. 6. Here, of the RGB data, only the color version of R, for example, will be described. The same applies to G and B, so their explanation will be omitted.

FIG. 6A is a diagram showing an example image 601 to be subjected to edge enhancement processing. In the image 601, for example, it is assumed that the shaded area indicates an area where the R signal value is 200, and the area without the hatching (non-hatched area) indicates an area where the R signal value is 255. Further, FIG. 6(b) is an enlarged view of an edge portion 602 shown by 3×3 pixels in the image 601 of FIG. 6(a). In the edge portion 602 shown in FIG. 6B, the pixel of interest to be processed is the center pixel 612 of the edge portion 602. Further, FIG. 6(c) is a diagram showing the weight for each 3×3 pixel of the edge portion 602 shown in FIG. 6(b), and the numerical value written in each pixel indicates the weight value. represents.

The filter processing in the filter processing unit 212 is performed by multiplying each 3×3 pixel of the edge portion 602 by the weight value shown in FIG. This is sharpness processing that uses the signal value of the pixel 612 (the pixel of interest). This sharpness processing is expressed by the following equation (1).

(Signal value of center pixel) = 200 x 0 + 200 x (-1) + 255 x 0 + 200 x (-1) + 200 x 5 + 255 x (-1) + 200 x 0 + 200 x (-1) + 255 x 0 = 145 Formula (1)

The 3×3 pixel edge portion 603 shown in FIG. 6(d) represents the 3×3 pixels after sharpness processing has been performed such that (signal value of center pixel)=145 according to equation (1). It is a diagram. In the edge portion 603 after the sharpness processing has been performed, the center pixel 613 becomes darker due to the sharpness processing, so the center pixel 613 in FIG. 6(d) is darker than the center pixel 612 in the edge portion 602 in FIG. 6(d). The number of diagonal lines in the shaded area is increased to indicate that the area is also darker.

Since such processing is performed on all pixels of the image 601 in FIG. 6(a), the image after such processing is an image in which the edge portion 614 is darkened as shown in FIG. 6(e), In other words, the image 604 is edge-enhanced.
Although the explanation has been given above using the R color plate as an example, similar processing is performed for G and B as well. Although RGB is taken as an example here, other color spaces such as CMYK data can be similarly processed.

<Trapping process>
Next, as another example of the edge enhancement processing performed in S502, an example in which trapping processing by the trapping processing unit 213 is applied will be described with reference to FIG. 7.
Generally, the trapping process is performed after converting to CMYK, so if the color of the image is RGB, the trapping process is performed after converting to CMYK. Hereinafter, an example will be described in which the C and M color plates of CMYK are adjacent to each other.

FIG. 7A is a diagram showing an example image 701 to be subjected to trapping processing. In the image 701, it is assumed that the shaded area indicates an area where the pixel value of C among CMYK is 128, and the dotted area indicates an area where the pixel value of M among CMYK is 128. FIG. 7(b) is an enlarged view of an edge portion 702 represented by 3×3 pixels in the image 701 of FIG. 7(a). Further, in FIG. 7B, it is assumed that an edge portion 721 shows only the C color portion of CMYK, and an edge portion 722 shows only the M color portion. In the edge portion 702 shown in FIG. 7B, the pixel of interest to be processed is the center pixel 712 of the edge portion 702. Further, FIG. 7(c) is a diagram showing the weight for each 3×3 pixel of the edge portion 702 shown in FIG. 7(b), and the numerical value written in each pixel indicates the weight value. represents.

The trapping process performed by the trapping processing unit 213 is a process in which, in each 3×3 pixel of the edge portion 702 shown in FIG. be. For this reason, when there is a color plate of C in the pixel of interest (center pixel 712), as in the edge portion 721 illustrated in FIG. No processing is performed.

On the other hand, since there is no M color plate in the pixel of interest (center pixel 712) in the edge portion 722 that shows only the M color plate, trapping processing that takes the value of the M color plate from the surroundings of the pixel of interest is performed. It will be done. That is, here, the trapping process that takes the value of the M color plate from the surroundings is performed as shown in FIG. 7(c) for each 3×3 pixel of the edge portion 722 shown in FIG. 7(b). By applying weights, the central pixel value is obtained. The pixel value of M of the center pixel obtained by this trapping process becomes a pixel value expressed by arithmetic processing such as equation (2).

(M pixel value of center pixel) = 128 x 100% = 128 Formula (2)

Then, when the edge portion 722 after weighting and the C color plate of the edge portion 721 are combined, as shown in the edge portion 703 in FIG. =(C,M,Y,K)=(128,128,0,0).

The trapping process is performed on all pixels of the image 701 in FIG. 7(a). As a result, the image after the trapping process is such that the C color plate and the M color plate overlap at the boundary 714 between the C color plate and the M color plate, as shown in the image 704 in FIG. 7(e). The image becomes The color conversion for converting CMYK data to K data can be done as C+M+Y+K=K', and the C color plate portion other than the boundary between the C color plate and the M color plate is (C, M , Y, K)=(128,0,0,0)→(128). Further, the boundary between the C color plate and the M color plate becomes (C, M, Y, K)=(128,128,0,0)→(256).

<Processing from print data acquisition to preview>
Next, a process will be described in which a preview image is generated and previewed based on the accumulated images in the case where the discriminability improvement process by the edge enhancement process as described above is performed. Whether or not to perform the distinctiveness improvement process is specified by a distinctiveness improvement process designation command included in the print data supplied from the host PC 119. The process of previewing an image based on print data when the discriminability improvement process is specified will be described below with reference to the flowchart of FIG. 8. The flowchart in FIG. 8 shows the flow of processing in the image forming apparatus 101 from acquisition of print data to previewing.

First, in S801, the image forming apparatus 101 acquires the above-described print data from the host PC 119.
Next, in step S<b>802 , the command analysis unit 204 of the command processing unit 102 analyzes a drawing command and a control command from the print data acquired from the host PC 119 . That is, the command analysis unit 204 acquires information such as color mode designation, color conversion designation, discrimination improvement processing designation, and designation of whether to save an image from the control command. The command analysis unit 204 also acquires attribute information of each object in the print data from the drawing command.

Next, in S803, the command execution unit 206 executes RIP processing and generates a raster image. Here, if the color mode is specified as color, the command execution unit 206 generates a color raster image. Further, if the color mode is specified as monochrome and the discriminability improvement process is not specified, the command execution unit 206 generates a monochrome raster image. On the other hand, when the color mode is specified as monochrome and the discriminability improvement process is specified, the command execution unit 206 generates a color raster image.

Next, in S804, the accumulation control unit 103 determines whether to save (accumulate) each data of the image, attribute information, and command analysis result. A determination as to whether or not to save this data is made based on the results analyzed by the command analysis unit 204 in S802. That is, if there is no designation to store the image, the storage control unit 103 determines not to store the image in S804, and the process of the CPU 105 advances to S809. Proceeding to S809, the image processing unit 104 executes printer image processing. On the other hand, if there is a designation to store the image, the storage control unit 103 determines to store it in S804, and the process of the CPU 105 advances to S805. Then, proceeding to S805, the accumulation control unit 103 causes the auxiliary storage device 111 to store the raster image, attribute information, and command analysis results.

After S805, in S806, the accumulation control unit 103 refers to the saved command analysis results and determines whether or not discriminability improvement processing is specified.
If it is determined in S806 that the discriminability improvement process is not specified, the process of the CPU 105 proceeds to S808. Here, if the discriminability improvement process is not specified, the raster image generated in S803 and saved in S805 has already been converted to monochrome. Therefore, in step S808, the accumulation control unit 103 sends the stored monochrome raster image to the preview control unit 225, and the preview control unit 225 displays the image on the display unit 125 as a preview image.

On the other hand, if it is determined in S806 that the discriminability improvement process is specified, the process of the CPU 105 advances to S807. Here, if the discriminability improvement process is specified, the raster image generated in S803 and saved in S805 is in color. Therefore, when the process advances to S807, the accumulation control unit 103 sends the color raster image to the image processing unit 104, and the image processing unit 104 performs processing to generate a preview image from the color raster image. Thereafter, the process of the CPU 105 advances to S808.

FIG. 9 is a flowchart showing the flow of preview image generation processing in S807.
First, in S901, the image processing unit 104 acquires the raster image and attribute information read from the auxiliary storage device 111 via the storage control unit 103. Then, the image processing unit 104 determines whether the attribute information indicates an object with a graphic attribute or a text attribute. In the case of the example shown in FIG. 4A described above, the attribute information for the graphic 402 and the characters 403 indicates the graphic attribute and the character attribute, so the processing of the image processing unit 104 proceeds to S903. On the other hand, in the case of the image 404 in FIG. 4A, the attribute information does not indicate a graphic attribute or a text attribute, so the process of the image processing unit 104 proceeds to S902.

If the process advances to step S903 because the attribute information indicates a graphic attribute or text attribute, the image processing unit 104 processes the image processing unit 104 because the areas of those graphic or text objects are target areas for the discriminability improvement process. Converting the image to a first image. In this embodiment, it is assumed that the conversion to the first image is, for example, to change the color value of each pixel in the image of the region to the color value of a specific color. On the other hand, if the attribute information is an image attribute and the process advances to step S902, the area of that image attribute is not a target area of the discriminability improvement process, so the image processing unit 104 converts the image of that area into a second image. do. In this embodiment, it is assumed that the conversion to the second image means, for example, converting the image into a gray value calculated by weighting the RGB values in the image of the region.

In the case of this embodiment, the color value of a specific color when converting a graphic or character image in S903 is magenta (255, 0, 255), for example, but is determined based on the pixel value of the raster image. It may also be a color value. Further, in the case of this embodiment, the gray value when converting the image attribute area in S902 is a gray value calculated by weighting the RGB values of the raster image, for example, (128, 128, 128), etc. It may be a specific predetermined gray color value. The image generated by the image processing unit 104 in this manner is stored as a preview image in the RAM 107 separately from the raster image by the storage control unit 103, and then displayed on the display unit 125 by the preview control unit 225 in S808. Is displayed.

FIG. 10A is a diagram showing an example of a preview screen displayed on the display unit 125 in the first embodiment. As an example, a preview area 1000, an explanation display area 1003, and a return button 1004 are displayed on the preview screen. A preview image generated by the image processing unit 104 is displayed in the preview area 1000. In the case of the image example in FIG. 4A, the graphic 402 and character 403 areas are displayed as a color value area of the specific color described above (color area 1001), and the image 404 is a gray area 1002 that has been converted into monochrome. will be displayed as . Further, in the explanation display area 1003, an explanation regarding the preview image displayed in the preview area 1000 is displayed. In the case of this embodiment, the explanation display area 1003 displays an explanation saying "Distinguishability improvement processing will be applied to colored parts." In other words, this explanatory text indicates that the graphics and characters in the color area 1001 (the area of the graphics 402 and characters 403 illustrated in FIG. 4A) are subjected to discrimination improvement processing. The return button 1004 is a button that is pressed by touch or the like when the user instructs to return from the preview screen to the previous screen. When the return button 1004 is pressed (touched, etc.), the preview control unit 225 finishes displaying the preview screen and performs processing to return to the screen displayed in the previous process. Note that if the preview area 1000 does not have a color area, the explanation display area 1003 may display a sentence indicating that the discrimination improvement process is not performed on the image in the preview area. Alternatively, only the explanatory text may be displayed without displaying the preview area 1000.

The explanation returns to the flowchart of FIG.
After it is determined in step S804 that the data is not to be saved and printer image processing is executed in step S809, the CPU 105 determines in step S810 whether processing for all pages has been completed. Then, if the processing for all pages is not completed and there are unprocessed pages, the CPU 105 returns the processing to S801. As a result, from then on, the same process as described above is performed on the unprocessed page. On the other hand, if it is determined in S810 that the processing of all pages has been completed, the CPU 105 ends the processing of the flowchart of FIG.

As described above, according to the first embodiment, even if the image after RIP processing is different from the output image (printed image) of the image forming apparatus, the image can be processed without making the user feel uncomfortable and It becomes possible to display a preview that is useful to the user. In particular, when the function set in the printer driver 202 is realized by printer image processing, and the area where the set function is valid is not the entire image, but the function is adaptively determined during image processing, Implementing a preview display is useful.

In other words, according to the present embodiment, when previewing an accumulated image, a preview image is generated in which an area that undergoes characteristic image processing in the image forming apparatus is the first image, and an area that is not subjected to the characteristic image processing is the second image. By doing so, it becomes possible to provide a useful preview to the user.
In addition, in the description of this embodiment, an example was explained in which discriminability improvement processing is performed when converting color to monochrome, but trapping processing, thickening processing, text jitter correction processing, etc. realized by printer image processing, etc. A similar preview is possible even when other image processing is performed.

In addition, in this embodiment, conversion to an image with color values of a specific color is cited as an example of conversion to the first image, and conversion to a gray image is cited as an example of conversion to the second image. and the second image are not limited to these examples. For example, if it is possible to clearly show to the user that the preview image is a target area for predetermined image processing such as discriminability improvement processing, or that it is not a target area for predetermined image processing, the above-mentioned color or gray image It is also possible to convert to other images. For example, the first image and the second image may be images that can be distinguished by the user, such as images of specific or arbitrarily selected patterns or patterns, or may be images of symbols, marks, characters, etc. may be used.

<Second embodiment>
In the first embodiment described above, the discriminability improvement process is performed in the image processing unit 104 of the image forming apparatus 101, so the images stored in the auxiliary storage device 111 are color images. In contrast, in the second embodiment, an example will be given in which the discriminability improvement process is performed during RIP processing. Therefore, in the case of the second embodiment, a case will be described using an example in which some of the images to be stored are monochrome. Note that the configuration in the second embodiment is similar to the configuration shown in FIGS. 1 and 2 of the first embodiment described above, and therefore illustration thereof will be omitted. Furthermore, since the general process flow from acquisition of print data to preview in the image forming apparatus 101 of the second embodiment is the same as that shown in FIG. 8 described above, illustration thereof is also omitted. In the second embodiment, differences from the first embodiment will be mainly explained.

In the case of the second embodiment, when converting from color to monochrome, all color values (for example, RGB values) used for characters and graphics in the image are extracted. In the discriminability improvement process of the second embodiment, these color values are assigned at intervals from 0 to 255, which can be taken as gray values. Note that the second embodiment will be described on the assumption that the bit depth of the image is an 8-bit image. In the second embodiment, by performing a process of assigning each color value to a value of 0 to 255 that can be taken as a gray value at intervals, it is possible to ensure the difference in shading between objects of the first attribute, and as a result, This makes it possible to improve discrimination.

Here, when extracting all the RGB values of text and graphics from the entire image, rather than obtaining RGB values for each pixel of the raster image after RIP processing, the RGB values described in the PDL before RIP processing are extracted. It is more efficient to obtain RGB values for each object. Also, when converting RGB values into gray values corresponding to them, it is more efficient to convert the corresponding RGB values into the desired gray values in a batch for each object described in PDL than to convert it in units of pixels. Can be processed.

Therefore, in the case of the second embodiment, the image forming apparatus 101 executes the discriminability improvement process shown in the flowchart of FIG. 11 during RIP processing. However, for objects with the second attribute to which the discriminability improvement processing is not applied, such as the image 404 in FIG. 4A, the command execution unit 206 receives the objects as color PDL data. RIP processing is performed as follows. Therefore, in the case of the second embodiment, in the raster image after RIP processing, the graphics 402 and characters 403 become gray images with enhanced discrimination through discrimination improvement processing, while the image 404 becomes a color image. ing. Therefore, when previewing in the second embodiment, a gray image with improved discrimination between the graphics 402 and characters 403 is set as a color image (first image), and a color image of the image 404 is converted into monochrome and a gray image (second image) is used. image).

<Color to monochrome conversion to improve discrimination in second embodiment>
First, the discriminability improvement process in the second embodiment will be explained using the flowchart of FIG. 11.
In step S1101, the command analysis unit 204 of the image forming apparatus 101 performs command analysis of the print data acquired from the host PC 119, and further analyzes the colors specified by the color setting command for objects with graphic attributes and text attributes in the image. Extract the value. Then, the command analysis unit 204 performs color value list creation processing such as adding these extracted color values to a color value list 1201 as shown in FIG. 12(a). The color value list 1201 holds extracted RGB values.

Taking the input image 401 shown in FIG. 4(a) as an example, in the color value list creation process, RGB color values (255, 128, 128) of the graphic 402 are extracted, and these color values are numbered. It is registered in the color value list 1201 as a color value of 1. Similarly, the RGB color values (153, 153, 255) of the character 403 are also extracted, and the color values are No. It is registered in the color value list 1201 as color value 2. Then, the command analysis unit 204 adds gray values (Gray) obtained by NTSC-converting each RGB value of the color value list 1201 to the list. In the case of the color value list 1201 illustrated in FIG. 12(a), the number corresponding to the graphic 402. 166 is the gray value of 1, which corresponds to the number 403. 165 is registered as the gray value of 2. After the color value list 1201 of all graphic attribute and text attribute objects in the image is completed by such color value list creation processing, the command analysis unit 204 stores the color value list 1201 in the RAM 107.

Next, in S1102, the image processing unit 104 performs discriminability improvement processing to modify the gray values registered in the color value list 1201 stored in the RAM 107 to gray values that have discriminability. In the case of the color value list 1201 in FIG. 12(a), No. The gray value of No. 1 (gray value of graphic 402) is 166, and No. The gray value of 2 (gray value of character 403) is 165, and the difference is only 1, so it is considered that there is almost no distinguishability. Therefore, the image processing unit 104 executes discrimination improvement processing to widen the difference between the gray values 166 and 165. Although the details will be described later, in the discriminability improvement process in the second embodiment, the gray value is between 0 (black) and 255 (white), and the gray value difference from the white value of 255 and the black value of 0 is considered. Adjustment processing is performed to widen the difference.

Various methods can be considered for discriminability improvement processing by gray value adjustment as in the second embodiment, but as an example, when there are only two objects, the difference between the gray values of the two objects is set to a predetermined value or more. One example is a process that expands the Note that the minimum predetermined value required as a gray value difference that can be discriminated is, for example, 15 to 20, although it depends on the performance of the image forming apparatus 101. Therefore, the predetermined value or more means 15 to 20 or more. It is desirable that the value is . In this embodiment, the value of the difference after expanding the difference in gray values between two objects is set to 70, for example. In addition, when processing to increase the difference between the gray values of two objects beyond a predetermined value, the difference between the gray value of one of those two objects and 255 (white), and the difference between the gray value of the other and 0 Adjust to maintain the difference between (black) and the ratio between. Note that in the case of this embodiment, the gray values of the two objects are 166 and 165, as illustrated in FIG. 12(a). In this case, 89 is the difference between 255 (white) and one gray value of 166 (255-166), and the difference between 0 (black) of the other gray value of 165 (165-0) The ratio between 165 and 165 is maintained.

In this case, out of 255 possible intervals between 255 and 0, the difference between the gray value of the two objects and 255 (white) or 0 (black) after subtracting the predetermined value from 255 All you have to do is find out how much difference there is between the intervals. For example, if the value to widen the difference is 70 and the gray values of two objects are 166 and 165, 255-166 (=89) and 165-0 (=165) are 185, which is 255 minus 70. All you have to do is find out how much difference there is between each interval. In this embodiment, for example, by using the following equations (3) to (5), the difference between the gray values of two objects is increased to a predetermined value or more, and the gray value and white, and the gray value and black are Maintain the ratio between the difference.

(255-166)/255=(255-X1)/(255-70) Formula (3)
From this formula (3), X1≒190,
(165-0)/255=(X2-0)/(255-70) Formula (4)
From this equation (4), X2≈120.
The relationships between 255 (white), 0 (black), 166 and 165, and 190 and 120 are expressed by equation (5).
(255-166):(165-0)≒(255-190):(120-0) Formula (5)

According to these equations (3) to (5), out of the 255 possible intervals between 255 (white) and 0 (black), the gray value of 166,165 between the two objects increases the difference to 70. The calculated gray value is 190,120. Furthermore, the gray values of 190 and 120, 255 (white), and 0 (black) of these two objects maintain the ratio of the difference from 0 (black) and 255 (white).

According to the second embodiment, the approximate gray values of 166, 165 of the two objects shown in FIG. will be corrected. In other words, the difference between the gray values of these two objects is large, so that the distinguishability is improved. In the case of the second embodiment, the difference in gray value after correction is 70, which is larger than the minimum necessary predetermined value of 15 to 20. Therefore, in this embodiment, these two objects can be easily distinguished.

The explanation returns to the flowchart of FIG. 11.
When the process proceeds to S1103 after the discriminability improvement process in S1102, the command execution unit 206 executes RIP processing and converts the PDL to a raster image. At this time, the command execution unit 206 reads out and refers to the color value list 1201 stored in the RAM 107 while converting the RGB values into gray values. In the case of this embodiment, in the raster image generated in the process of S1103, the graphic 402 and characters 403 illustrated in FIG. 4A are gray, but the image 404 remains in color.

Next, in S1104, the color conversion processing unit 211 converts the color image 404 to gray. This means that all objects have been converted to gray. In this example as well, when the input image to the color conversion processing unit 211 is RGB, the color conversion processing unit 211 calculates the gray value by weighting each of R, G, and B, and then inverts the value to increase the density. Convert to the value of K, which is a signal value. Further, when the input image to the color conversion processing unit 211 is CMYK, the color conversion processing unit 211 converts it into a K signal value. Note that the color conversion processing unit 211 also inverts the gray value and converts it into a density signal value if it remains a luminance signal value.
Although only the discriminability improvement processing has been described above, other necessary image processing is also executed as appropriate, and the image data after the image processing is transmitted to the image output unit 109.

In the second embodiment, as explained above, a color value list for converting RGB values into gray values is created before RIP processing, and when the gray values have low discriminability, the discriminability is Modify the color value list for converting RGB values to gray values to improve performance. As described above, according to the present embodiment, the discrimination property can be improved by converting to gray values while referring to the color value list during RIP processing.

<Preview image generation processing in the second embodiment>
The image forming apparatus 101 of the second embodiment generates a preview image using an image after performing the discrimination improvement process during the RIP process as described above. As a result, in the second embodiment, the image is not filled with uniform values like the color area 1001 in FIG. 10(a) of the first embodiment, but is similar to the input image 401 in FIG. 4(a). A preview image of what it will look like will be generated.

The preview image generation process in the second embodiment will be described below using the flowchart of FIG. 8 described above. Note that, in the flowchart of FIG. 8 according to the second embodiment, descriptions of processes that are generally similar to those of the first embodiment will be omitted, and herein, the preview image generation process of S807 will be mainly described.

In the case of the second embodiment, in the case of a raster image stored in the auxiliary storage device 111 by the accumulation control unit 103, the graphics 402 and characters 403 illustrated in FIG. are converted to gray values. Therefore, the image processing unit 104 uses this gray value to determine the color value for the preview image. As a specific method for determining the color value, for example, if the color value is determined to be magenta, as shown in FIG. 12(c), the gray value (Gray) is set as the value of G, and this The magenta color value is determined from the value and the R and B values. In the example of FIG. 12(c), the number corresponding to the graphic 402. 1 has the magenta (255, 190, 255) number corresponding to the character 403. 2 is applied with magenta (255, 120, 255).

The image generated by the image processing unit 104 in this manner is stored as a preview image by the storage control unit 103 in the RAM 107, for example, separately from the raster image, and then, in S808, the preview control unit 225 saves the image on the display screen. 125.

FIG. 10(b) is a diagram showing an example of a preview screen displayed on the display unit 125 in the second embodiment. A preview area 1005, an explanation display area 1003, and a return button 1004 are displayed on the preview screen, as in the example of FIG. 10(a) described above. A preview image generated by the image processing unit 104 of the second embodiment is displayed in the preview area 1005. Further, in the explanation display area 1003, an explanation similar to the example of FIG. 10(a) is displayed. The return button 1004 is a button used when the user instructs to return to the previous process from the preview screen, as in the example of FIG. 10(a).

In FIG. 10B, the preview image in the preview area 1005 is an image that includes a graphic portion 1006 corresponding to the graphic 402 and a character portion 1007 corresponding to the character 403. That is, in the case of the second embodiment, in the first image in the area of objects with graphic attributes and text attributes, the magenta value of the graphic part 1006 and the magenta value of the text part 1007 are different, and the shading is also different from the input image. This is a close-up image. On the other hand, the gray area 1008 corresponding to the image 404 that is the second image in the image attribute area is not a uniform gray value, but a gray value that has been converted into monochrome by NTSC conversion, and is a gray value that is close to the image to be printed. It is. As a result, the preview image becomes an image that is displayed in the preview area 1005 in FIG. 10(b), and becomes a preview image that is close to the input image 401, making it easier for the user to understand.

As described above, according to the second embodiment, it is possible to display a preview image that looks closer to the input image 401 than in the first embodiment, and it is possible to perform a preview that is useful for the user. becomes possible.

The present invention provides a system or device with a program that implements one or more functions of the embodiments described above via a network or a storage medium, and one or more processors in a computer of the system or device reads and executes the program. This can also be achieved by processing. It can also be realized by a circuit (for example, ASIC) that realizes one or more functions. The above-described embodiments are merely examples of implementation of the present invention, and the technical scope of the present invention should not be construed as limited by these embodiments. That is, the present invention can be implemented in various forms without departing from its technical idea or main features.

The disclosure of each embodiment includes the following configuration, method, and program.
(Configuration 1)
storage means for storing an image generated from print data through processing by a raster image processor, and object attributes and commands acquired based on the print data;
processing means for performing image processing on the accumulated images;
generating means for generating a preview image based on the accumulated images;
preview means for displaying the preview image;
has
When the command indicates execution of predetermined image processing, the generating means sets the region of the accumulated image corresponding to the object of the first attribute to the first image in a specific color. An image processing device characterized by generating a preview image.
(Configuration 2)
The generating means generates the preview image in which an area corresponding to an object having a second attribute different from the first attribute among the accumulated images is set as a second image different from the specific color. The image processing device according to configuration 1.
(Configuration 3)
The image processing device includes an accumulation unit for accumulating an image generated from print data through processing by a raster image processor, and object attributes and commands acquired based on the print data;
processing means for performing image processing on the accumulated images;
generating means for generating a preview image based on the accumulated images;
preview means for displaying the preview image;
has.
When the command indicates execution of predetermined image processing, the generating means causes a region of the accumulated image corresponding to the object of the first attribute to be subjected to the predetermined image processing. The preview image is generated as a first image showing. An image processing device characterized by this.
(Configuration 4)
The generating means defines an area of the accumulated images corresponding to an object having a second attribute different from the first attribute as a second image indicating that the area is not a target of the predetermined image processing. The image processing device according to configuration 3, wherein the image processing device generates a preview image.
(Configuration 5)
The first image corresponding to the area of the object with the first attribute is a specific color or an image with a color value determined according to the color value of the accumulated image,
The second image corresponding to the area of the object with the second attribute is a gray value that is a specific gray value different from the specific color or a gray value that is calculated by weighting the RGB values of the accumulated image. The image processing device according to configuration 2 or 4, wherein the image has a value of .
(Configuration 6)
When the command indicates monochrome conversion of the accumulated image and indicates execution of the predetermined image processing, the generating means performs the following control. That is, the generating means generates the preview image by setting an area corresponding to the object of the first attribute as an image of the color value, and setting an area corresponding to the object of the second attribute as an image of the gray value. The image processing device according to configuration 5, characterized in that the image processing device generates.
(Configuration 7)
Any one of configurations 2, 4, 5, and 6, wherein the object with the first attribute is an object with a graphic attribute and a text attribute, and the object with the second attribute is an object with an image attribute. The image processing device described in .
(Configuration 8)
Any one of configurations 1 to 7, wherein the preview means displays, together with the preview image, an explanatory text indicating that the predetermined image processing is performed on the area of the object having the first attribute. 1. The image processing device according to configuration 1.
(Configuration 9)
Any one of configurations 1 to 8, wherein the predetermined image processing includes processing for increasing the discriminability between adjacent objects of the first attribute when the accumulated image is converted to monochrome. 1. The image processing device according to configuration 1.
(Configuration 10)
10. The image processing apparatus according to configuration 9, wherein the processing for increasing the discriminability is processing for emphasizing an edge of a boundary between the adjacent objects.
(Configuration 11)
In configuration 9, the processing for increasing the discriminability is processing for determining a value such that a difference in gray value between the adjacent objects after the monochrome conversion is equal to or greater than a predetermined value. The image processing device described.
(Configuration 12)
In the process of increasing the discriminability, the ratio between the difference between one gray value and white, which is equal to or greater than the predetermined value, and the difference between the other gray value and black is adjusted to be maintained. The image processing device according to configuration 11, characterized in that:
(Method 1)
an accumulation step of accumulating an image generated from print data through processing by a raster image processor, and object attributes and commands acquired based on the print data;
a processing step of performing image processing on the accumulated images;
a generation step of generating a preview image based on the accumulated images;
a preview step of displaying the preview image;
has
When the command indicates execution of predetermined image processing, in the generation step, the area of the accumulated image corresponding to the object with the first attribute is made into the first image in a specific color. An image processing method characterized by generating a preview image.
(Method 2)
The image processing method includes an accumulation step of accumulating an image generated from print data through processing by a raster image processor, and object attributes and commands acquired based on the print data;
a processing step of performing image processing on the accumulated images;
a generation step of generating a preview image based on the accumulated images;
a preview step of displaying the preview image;
has.
If the command indicates execution of predetermined image processing, in the generation step, the area corresponding to the object of the first attribute in the accumulated image is subjected to the predetermined image processing. The preview image is generated as a first image showing. An image processing method characterized by this.
(Program 1)
A program for causing a computer to function as the image processing device according to any one of configurations 1 to 12.

101: Image forming device, 102: Command processing unit, 103: Accumulation control unit, 104: Image processing unit, 203: Command determination unit, 204: Command analysis unit, 206: Command execution unit, 212: Filter processing unit, 213: Trapping processing unit, 225: Preview control unit

Claims (16)

storage means for storing an image generated from print data through processing by a raster image processor, and object attributes and commands acquired based on the print data;
processing means for performing image processing on the accumulated images;
generating means for generating a preview image based on the accumulated images;
preview means for displaying the preview image;
has
When the command indicates execution of predetermined image processing, the generating means sets the region of the accumulated image corresponding to the object of the first attribute to the first image in a specific color. An image processing device characterized by generating a preview image. The generating means generates the preview image in which an area corresponding to an object having a second attribute different from the first attribute among the accumulated images is set as a second image different from the specific color. The image processing apparatus according to claim 1, characterized in that: storage means for storing an image generated from print data through processing by a raster image processor, and object attributes and commands acquired based on the print data;
processing means for performing image processing on the accumulated images;
generating means for generating a preview image based on the accumulated images;
preview means for displaying the preview image;
has
When the command indicates execution of predetermined image processing, the generating means indicates that the area corresponding to the object of the first attribute in the accumulated image is to be subjected to the predetermined image processing. An image processing device that generates the preview image as a first image. The generating means defines an area of the accumulated images corresponding to an object having a second attribute different from the first attribute as a second image indicating that the area is not a target of the predetermined image processing. The image processing device according to claim 3, wherein the image processing device generates a preview image. The first image corresponding to the area of the object with the first attribute is a specific color or an image with a color value determined according to the color value of the accumulated image,
The second image corresponding to the area of the object with the second attribute is a gray value that is a specific gray value different from the specific color or a gray value that is calculated by weighting the RGB values of the accumulated image. 5. The image processing apparatus according to claim 2, wherein the image has a value of . When the command indicates monochrome conversion of the accumulated image and indicates execution of the predetermined image processing, the generating means converts the area corresponding to the object of the first attribute into the color value. 6. The image processing apparatus according to claim 5, wherein the preview image is generated by setting the image of the object having the second attribute to the image of the gray value. 5. The image processing apparatus according to claim 2, wherein the object with the first attribute is an object with a graphic attribute and a text attribute, and the object with the second attribute is an object with an image attribute. 4. The preview means displays, together with the preview image, an explanatory text indicating that the predetermined image processing is performed on the area of the object having the first attribute. image processing device. 4. The predetermined image processing includes processing for increasing the discriminability between adjacent objects of the first attribute when the accumulated image is converted to monochrome. image processing device. 10. The image processing apparatus according to claim 9, wherein the processing for increasing the discriminability is processing for emphasizing an edge of a boundary between the adjacent objects. 10. The process of increasing the discriminability is a process of determining a value such that a difference in gray value between the adjacent objects after the monochrome conversion is equal to or greater than a predetermined value. The image processing device described in . In the process of increasing the discriminability, the ratio is adjusted to maintain the ratio between the difference between one gray value and white, which is equal to or greater than the predetermined value, and the difference between the other gray value and black. The image processing device according to claim 11. an accumulation step of accumulating an image generated from print data through processing by a raster image processor, and object attributes and commands acquired based on the print data;
a processing step of performing image processing on the accumulated images;
a generation step of generating a preview image based on the accumulated images;
a preview step of displaying the preview image;
has
When the command indicates execution of predetermined image processing, in the generation step, the area of the accumulated image corresponding to the object with the first attribute is made into the first image in a specific color. An image processing method characterized by generating a preview image. an accumulation step of accumulating an image generated from print data through processing by a raster image processor, and object attributes and commands acquired based on the print data;
a processing step of performing image processing on the accumulated images;
a generation step of generating a preview image based on the accumulated images;
a preview step of displaying the preview image;
has
When the command indicates execution of predetermined image processing, in the generation step, the area corresponding to the object of the first attribute in the accumulated image is indicated to be subjected to the predetermined image processing. An image processing method characterized by generating the preview image as a first image. computer,
storage means for storing an image generated from print data through processing by a raster image processor, and object attributes and commands acquired based on the print data;
processing means for performing image processing on the accumulated images;
generating means for generating a preview image based on the accumulated images;
preview means for displaying the preview image;
has
When the command indicates execution of predetermined image processing, the generating means sets the region of the accumulated image corresponding to the object of the first attribute to the first image in a specific color. A program that functions as an image processing device that generates preview images. computer,
storage means for storing an image generated from print data through processing by a raster image processor, and object attributes and commands acquired based on the print data;
processing means for performing image processing on the accumulated images;
generating means for generating a preview image based on the accumulated images;
preview means for displaying the preview image;
has
When the command indicates execution of predetermined image processing, the generating means indicates that the area corresponding to the object of the first attribute in the accumulated image is to be subjected to the predetermined image processing. A program that functions as an image processing device that generates the preview image as a first image.

Images