JPH11341265A - Method and device for picture processing - Google Patents

Abstract

PROBLEM TO BE SOLVED: To prepare a mosaic picture with a decreased density difference from an original picture in a mosaic picture as a whole by having a density difference between a division area of the original picture and a material picture distributed in a peripheral area. SOLUTION: This device is a picture processor which combines plural material pictures into a mosaic pattern and generates a mosaic picture, and it divides an original picture into plural areas (S31) and calculates an average density of each area of these divided areas (S32). Each average density of stored plural material pictures is calculated (S33), the material picture to be allocated to each area is decided (S37) in accordance with each average density of these operated areas and that of the plural material pictures, a difference of the average density between the decided material picture and the area concerned is obtained (S38), and is distributed to a area nearby the area (S36).

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing method and apparatus for generating a mosaic image by combining a plurality of material images in a mosaic manner.

[0002]

[Prior art]

[0003] The mosaic is widely known as "a technique in which small pieces of stone, glass, marble, etc. of various colors are combined, set in a floor, a wall, etc., and designed, or a technique thereof" (Sanseido Modern Japanese Dictionary). ing. Using this technique, many photographic images can be combined to form a design or one photographic image.

[0004]

However, when creating such a mosaic image, the original image is divided into a plurality of regions, and a material image (tile image) constituting the mosaic image is incorporated into each of these regions. Create a mosaic image with. However, if the material image close to the color of the divided area of the original image is not pasted, the quality of the created mosaic image will be completely different from the original image, and There was a problem that the quality also deteriorated.

The present invention has been made in view of the above conventional example, and has as its object to provide an image processing method and apparatus for creating a mosaic image by pasting a material image close to the color of the original image.

Another object of the present invention is to create a mosaic image in which the density difference between the original image and the original image is reduced by dispersing the difference in density between the divided region of the original image and the material image in peripheral regions. To provide an image processing method and apparatus.

Another object of the present invention is to provide an image processing method and apparatus for creating a high-quality mosaic image while maintaining the density characteristics of the original image.

[0008]

In order to achieve the above object, an image processing apparatus according to the present invention has the following arrangement.
That is, an image processing apparatus that generates a mosaic image by combining a plurality of material images in a mosaic manner, wherein a storage unit that stores the plurality of material images, and a plurality of material images that are stored in the storage unit. Calculating means for calculating an average density; calculating means for dividing an original image into a plurality of areas; calculating an average density of each of the divided areas; and calculating the average density of the area calculated by the calculating means. A material image determining unit that determines a material image to be assigned to the region according to an average density of each of the plurality of material images obtained by the calculating unit; and a material image determined by the material image determining unit and the region. Error diffusion means for diffusing the difference between the average densities into a region near the region.

In order to achieve the above object, the image processing method of the present invention comprises the following steps. That is, an image processing method for generating a mosaic image by combining a plurality of material images in a mosaic manner, and calculating a mean density of each of the plurality of material images, and dividing the original image into a plurality of regions Calculating the average density of each of the divided areas, and calculating the average density of the area calculated in the calculation step and the average density of each of the plurality of material images obtained in the calculation step. A material image determining step of determining a material image to be assigned to the region, and an error diffusion step of diffusing the difference between the material image determined in the material image determining step and the average density of the region to a region near the region. It is characterized by having.

[0010]

(Embodiment 1) Hereinafter, a preferred embodiment of the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 is a block diagram showing a configuration of a computer system for executing image processing according to an embodiment of the present invention.

In FIG. 1, a CPU 101 controls the entire system according to a program stored in a hard disk 106 and loaded into a RAM 105.
A keyboard 102 is used together with the mouse 102a to input various commands and data to the system according to the present embodiment. A display unit 103 includes, for example, a CRT and a liquid crystal. 104 is ROM, 105 is RAM
Thus, the storage unit in the system of the present embodiment is configured,
It stores programs executed by the system and data used by the system. 106 is a hard disk, 1
Reference numeral 07 denotes a floppy disk device, which constitutes an external storage device used in the file system of the system according to the present embodiment. 108 is a printer.

The hard disk 106 stores a plurality (P) of tile images serving as constituent elements of a mosaic image. M × N images selected from these are shown in FIG. 2 according to a program described later. So, M in the horizontal direction
A mosaic image is created by combining and arranging N images in the vertical direction. The mosaic image created in this way is
Stored as an image file on the hard disk 106,
The data is displayed on the CRT 103 or output to the printer 108 and printed.

FIG. 3 is a diagram for explaining the relationship between images used in the mosaic method.

In FIG. 3, an image 201 indicates a design or an image that is the basis for forming an image using the mosaic method. The image 202 is a mosaic image configured using a plurality of small images (tiles) by a mosaic method. The material image 203 is a material image used to compose the image 202. The number P of these material images is
Generally, the number of colors and textures required to compose the image 202 is a sufficiently large number that can be prepared. Here, for the sake of explanation, the size of each of the P material images is set to the same size as the tile, but the size of each material image does not necessarily need to match the size of the tile.
Also, it is not necessary that all P sheets have the same size. When the size of each material image is different as described above, the image 20
When pasting to the corresponding tile of No. 2, the size of the material image needs to be converted. Here, the number of sheets P is a number sufficiently larger than the above-mentioned M × N sheets.

Referring to FIGS. 4 to 7, appropriate M × N images are selected from P material images 203, and the original image 2 is selected.
A method for creating a mosaic image 202 based on 01 will be described.

FIG. 4 is a flowchart illustrating a method for generating a mosaic image in the computer system according to the present embodiment. A program for executing this processing is stored in the hard disk 106 and is loaded into the RAM 105 and executed.

First, in step S31, the original image 201 is divided into M × N areas (corresponding to tiles). As a result, M × N rectangular areas TL (0,0), TL (0,
1),..., TL (M−1, N−1) are generated.

FIG. 6 shows that the original image 201 is M × N (M = N).
4, (N = 5) rectangular areas are shown.

In FIG. 6, X and Y are images 20 respectively.
1 indicates the number of pixels in the horizontal and vertical directions.
1 is defined as M × N areas {TL (0,0),..., TL (M−
1, (N-1)} is the number of pixels in each region in the horizontal and vertical directions. Therefore, X (pixel) = p (pixel) ×
The relationship of M, Y (pixel) = q (pixel) × N holds.

FIG. 7 shows the configuration of each tile (region). Each tile is composed of p × q pixels of three primary colors {red (R), green (G), blue (B)}.

Next, in step S32, an area average density d comprising an average density of each of RGB in each of the M × N areas.
i and j are calculated according to the following equations. Here, di, j is a two-dimensional array of three-dimensional vectors, and di, j = (Ri, j, Gi, j, Bi,
j).

[0023]

(Equation 1)

Di, j = (ΣR / p · q, ΣG / p · q,
{B / p · q) Here, Σ indicates the sum of all pixels included in each area. Also, (0 ≦ i ≦ M−1, 0 ≦ j ≦ N−1).

In step S33, the average density tk of the material images is calculated on the basis of the RGB average densities of the P material images. This means that if the size of each material image is p '× q' (pixels),

[0026]

(Equation 2)

Tk = (ΣR / p ′ · q ′, ΣG / p ′ ·
q ′, ΣB / p ′ · q ′) (0 ≦ k ≦ P−1) Thus, the process proceeds to step S34, and the following step S34
In steps S42 to S42, the most appropriate material image for replacing each area is selected while employing a known error diffusion method used for binarizing the image.

First, in step S34, a horizontal counter variable i is initialized to "0". In the next step S35,
A vertical counter variable j is initialized to “0”. At this time, the error vector e, which is the accumulation of the errors calculated in the previous region, is initialized to (0, 0, 0). Next, proceeding to step S36, the average density di, of the area (i, j) is obtained.
An error vector e is added to j.

Di, j ← di, j + e Next, the process proceeds to step S37, where the average density di, j of the area is set.
Is selected as the material image k closest to. This selection method will be described later in detail with reference to the flowchart of FIG.

In this way, when the optimum material image for the region is selected, the process proceeds to step S38, where an error vector e based on the difference between the average density di, j of the region and the average density tk of the selected material image is calculated. calculate.

E ← di, j-tk The error vector e obtained in this manner is diffused in a subsequent process to an area located on the right side in the horizontal direction.

That is, in a step S39, the counter variable i is incremented (+1), and in a step S40, the value of the variable i is compared with M. Judge and step S4
Then, the counter variable j in the vertical direction is incremented by one so as to advance one in the vertical direction. Then, in step S42, the value of the variable j is compared with N, and if they are equal, the processing is terminated assuming that the processing has been completed for all M × N areas. Otherwise, the processing returns to step S35, and The processing for the horizontal area is executed.

If it is determined in step S40 that the value of the variable i is not equal to M, the process returns to step S36, and the process is performed on the region located on the right side in the horizontal direction.

Next, the process of selecting an optimum material image in step S37 of FIG. 4 will be described with reference to the flowchart of FIG.

[Selection of Optimum Material Image tk] FIG.
It is a flowchart which shows the determination process of the material image of step S37 of FIG.

First, in step S41, a counter variable h and a variable k for counting the number of material images are initialized to "0", and a variable D is initialized to a sufficiently large number. Next, proceeding to step S52, the average density dj, of the area (i, j) is obtained.
The difference Δd between i and the average density tk of the material image k is calculated according to the following equation.

Δd = ｛| square of di, jR−tkR |｝ + ｛|
square of di, jG-tkG | + square of di, jB-tKB | In this equation, | di, jR-tkR | is an error of the R component, and | di, jG-tkG | G component error, | di, jB-tKB
| Represents an error of the B component.

Then, the process proceeds to a step S53, wherein the difference Δd
Is compared with the value of the variable D. If Δd <D, step S
In step 54, the difference Δd is set to the variable D, and the value of the counter h is substituted for the variable k indicating the material image. Thereby, in step S54, the value of k indicating the material image when the error Δd is minimized is determined.

Subsequent to step S54 or in step S53, if Δd <D is not satisfied, the process proceeds to step S55, and the counter h is incremented (+1). Then, the process proceeds to step S56, where the value of the counter h is compared with the number (P) of the material images. If the values are equal, the process proceeds to step S47 assuming that the reference process for all the material images has been completed. Are repeated.

When the process proceeds to step S47, the image 2
The material image k to be pasted on the area 02 (i, j) is determined, and the decided material image is pasted on the area (i, j).

(Other Embodiment) Step S52 in FIG.
In the above, the difference calculation of the average density between the area of the original image and the material image was performed using the square distance calculation. However, the present invention is not limited to this, and simply calculates the absolute value (| di, jR− tkR |,
| Di, jG-tkG |, | di, jB-tKB |). In this case, although the calculation accuracy is lower than in the case of the square distance calculation, the processing speed can be increased.

Although the error e is diffused only in the right direction, the present invention is not limited to this. For example, the error e is diffused by half into each of the right region and the lower region. By applying various methods used in a general error diffusion method, it is possible to further improve the quality of a generated mosaic image.

Even if the present invention is applied to a system including a plurality of devices (for example, a host computer, an interface device, a reader, a printer, etc.), a device including one device (for example, a copying machine, a facsimile machine). Device).

Further, an object of the present invention is to provide a storage medium storing a program code of software for realizing the functions of the above-described embodiments to a system or an apparatus, and to provide a computer (or CPU) of the system or apparatus.
Or MPU) reads and executes the program code stored in the storage medium.

In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiment, and the storage medium storing the program code constitutes the present invention.

As a storage medium for supplying the program code, for example, a floppy disk, hard disk, optical disk, magneto-optical disk, CD-ROM, CD
-R, a magnetic tape, a nonvolatile memory card, a ROM, or the like can be used.

When the computer executes the readout program code, not only the functions of the above-described embodiment are realized, but also the OS (Operating System) running on the computer based on the instruction of the program code. ) Performs part or all of the actual processing, and the processing realizes the functions of the above-described embodiments.

Further, after the program code read from the storage medium is written in a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, based on the instruction of the program code, The case where the CPU of the function expansion board or the function expansion unit performs part or all of the actual processing and the functions of the above-described embodiments are realized by the processing is also included.

As described above, according to the present embodiment, it is possible to reduce the total amount of error between a material and a tile, and to improve the quality of a mosaic image.

[0050]

As described above, according to the present invention, the difference in density between the divided region of the original image and the material image is dispersed in the peripheral region, and the difference in density between the original image and the entire mosaic image is calculated. A reduced mosaic image can be created.

According to the present invention, a high-quality mosaic image can be created while maintaining the density characteristics of the original image.

[0052]

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of a computer system according to an embodiment.

FIG. 2 is a diagram illustrating a mosaic image.

FIG. 3 is a diagram illustrating a process of generating a mosaic image.

FIG. 4 is a flowchart illustrating a flow of a mosaic image creation process in the computer system of the present embodiment.

FIG. 5 is a flowchart showing a process of determining a material image in step S37 of FIG. 4;

FIG. 6 is a diagram illustrating an example of a mosaic image.

FIG. 7 is a diagram illustrating a color configuration of individual tiles forming a mosaic image.

[Explanation of symbols]

 101 CPU 102 Keyboard 102a Mouse 103 Display 104 ROM 105 RAM 106 Hard Disk 107 Floppy Disk 108 Printer

Claims (18)

[Claims] 1. An image processing apparatus for generating a mosaic image by combining a plurality of material images in a mosaic manner, comprising: storage means for storing a plurality of material images; and a plurality of material images stored in the storage means. Calculating means for calculating the average density of each of the following; calculating means for dividing the original image into a plurality of areas; calculating the average density of each of the divided areas; and calculating the average of the areas calculated by the calculating means. A material image determining unit that determines a material image to be assigned to the region according to a density and an average density of each of the plurality of material images obtained by the calculating unit; and a material image determined by the material image determining unit. An error diffusion unit for diffusing a difference between the average density of the region and a region near the region. 2. The method according to claim 1, wherein the material image determining unit assigns a material image having a minimum difference between an average density of the area and an average density of each of the plurality of material images to the area. The image processing device according to claim 1. 3. The image processing apparatus according to claim 1, wherein the calculating unit obtains an average density for each color component of the plurality of material images. 4. The image processing apparatus according to claim 1, wherein said calculating means obtains an average density for each color component of each area. 5. The image processing apparatus according to claim 1, wherein the error diffusion unit distributes the difference to a density of an area located on the right of the area. 6. The image processing apparatus according to claim 1, wherein the error diffusion unit distributes the difference to a density of an area located on the right and / or below the area. 7. An image processing method for generating a mosaic image by combining a plurality of material images in a mosaic manner, comprising: a calculating step of calculating an average density of each of the plurality of material images; A step of dividing the region into regions; a calculating step of calculating an average density of each of the divided regions; and an average density of the region calculated in the calculating step and each of the plurality of material images obtained in the calculating step. A material image determining step of determining a material image to be assigned to the area according to an average density; and an error for diffusing a difference between an average density of the material image determined in the material image determining step and the area to a neighboring area of the area. An image processing method, comprising: a diffusion step. 8. In the material image determining step, a material image in which a difference between an average density of the area and an average density of each of the plurality of material images is minimized is set as a material image to be assigned to the area. The image processing method according to claim 7. 9. The image processing method according to claim 7, wherein, in the calculating step, an average density for each color component of the plurality of material images is obtained. 10. The image processing method according to claim 7, wherein, in the calculating step, an average density of each color component in each of the regions is obtained. 11. The image processing method according to claim 7, wherein, in the error diffusion step, the difference is distributed to densities of an area located on the right of the area. 12. The image processing method according to claim 7, wherein, in the error diffusion step, the difference is distributed to densities of a region located on the right of and / or below the region. 13. A storage medium readable by a computer for storing a program for executing an image processing method for generating a mosaic image by combining a plurality of material images in a mosaic manner, wherein the average density of each of the plurality of material images is provided. A calculation process module for calculating the original image, a process module for dividing the original image into a plurality of regions, a calculation process module for calculating an average density of each of the divided regions, A material image determining step module for determining a material image to be assigned to the region according to an average density and an average density of each of the plurality of material images obtained by the calculating step module; An error diffusion process that diffuses the difference between the average density of the material image and the area to the area near the area Storage medium characterized by having a module. 14. The material image determination step module, wherein a material image that minimizes a difference between an average density of the area and an average density of each of the plurality of material images is a material image to be assigned to the area. Claim 13
A storage medium according to claim 1. 15. The storage medium according to claim 13, wherein said calculation step module calculates an average density for each color component of said plurality of material images. 16. The storage medium according to claim 13, wherein said calculation step module calculates an average density for each color component of each area. 17. The storage medium according to claim 13, wherein the error diffusion step module distributes the difference to a density of an area located on the right of the area. 18. The error diffusion process module according to claim 13, wherein the difference is distributed to the density of an area located on the right and / or below the area.
Storage media described in