KR20000038083A - Method for searching image using direction outline map - Google Patents

Abstract

PURPOSE: A method for searching an image using a direction outline map is provided to improve speed and efficiency of searching. CONSTITUTION: A method for searching an image using a direction outline map includes an image inputting procedure, a feature extracting procedure, a storing procedure, and a searching procedure. The image inputting procedure is to read a digitalized still image and moving image. The feature extracting procedure is to analyze the inputted image content to draw a direction outline map. The storing procedure is to store the drawn direction outline map. The searching procedure is to search required data based on the resemblance of the direction outline map to search a want data.

Description

Image Retrieval Using Directional Contour Map

The present invention relates to an image retrieval method using a directional contour map, and more particularly, to an image retrieval method using a directional contour map for retrieving multimedia data such as a still image or a moving image using a directional contour map feature extracted from an image.

In general, multimedia data such as still images and moving images have a complex nature in themselves. That is, it is generally impossible to look at a picture and find a word that can express the picture. However, the method of retrieving image data so far is to add a single word or a few words of annotation that can represent a picture, and to search later, the annotation information is searched by key in the same way as the existing text search. Has been used. However, because this method requires commenting for each picture, the work is too much and the subjectivity of the commenter is involved, so the commenter's point of view and the searcher who uses the information later coincide. If you don't, the search will fail. In order to make up for this drawback, a method of extracting various features from the contents of the image itself and retrieving images using such features has been developed.

However, due to the problem that such a method cannot cover the rich and complex meaning of an image, there has been a search for a method of searching the content of the image by a key. The methods that have been used so far have been various attempts such as using the color feature of the image, using the texture information, and segmenting the objects in the image. It can be seen that the harvest. However, since the search method based on the image features does not sufficiently represent what a person perceives at the current technology level, the user can easily search for an image desired by presenting various feature quantities to the user in addition to the above-described conventional feature quantities. You need to be able to.

In particular, in the case of using the color feature amount, the overall image atmosphere is relatively well reflected, whereas the feature of the object included in the image is not reflected at all. In the case of texture information, for example, the same grass Even though it shows considerable diversity according to illuminance and resolution, recognition methods that can cover such diversity have not been developed yet, so the retrieval method using this information also has its limitations.

On the other hand, the method of segmentation of an object in an image has a problem in that a target image capable of segmentation of an object is extremely limited, and thus, it is difficult to use a general still image or a video database.

Accordingly, the present invention provides a directional contour map which can improve the speed and efficiency of the search by searching the multimedia data more conveniently when the user searches the multimedia data by expressing the object information included in the image. The purpose is to provide a video retrieval method.

In order to achieve the above object, an image retrieval method using a directional contour map according to the present invention includes an image input process for reading a digitized still image and a video, and a direction contour map by analyzing contents of the input image. And a retrieving process for retrieving the desired data by verifying the similarity of the directional contour maps.

In addition, the present invention is an image input process for reading a digitized still image and video, a feature extraction process for analyzing the contents of the input image to create a direction contour map, and for storing the created direction contour map And a computer readable recording medium storing a program for executing a storing process and a searching process for searching for desired data by verifying the similarity of the directional contour map.

1 is a view for explaining an image retrieval method using a direction contour map according to the present invention.

2 is a view for explaining the operation of the feature extraction means;

3 shows an example of a 3x3 mask.

4 is a flowchart for explaining a direction contour map generation method.

<Explanation of symbols on the main parts of the drawing>

11: image input means 12: feature extraction means

13: storage means 14: search means

Hereinafter, with reference to the accompanying drawings will be described in detail the present invention.

1 is a view for explaining an image retrieval method using a directional contour map according to the present invention, FIG. 2 is a view for explaining the operation of the feature extraction means, FIG. 3 is a view showing an example of a 3 × 3 mask, and FIG. 4 is a flowchart for explaining a direction contour map generation method.

First, the image input means 11 reads a still image and a video file existing in the form of a file on a computer system in the form of a bitmap on a memory. The image of the bit metric type is input to the feature extraction means 12 to go through a series of feature extraction process.

The operation of the feature extraction means 12 is performed in three steps as shown in FIG.

In the first step, for all the pixels P0 on the bitmap stored in the memory, the mask shown in FIG. 3 is applied, and the difference between the pixel values in the horizontal and vertical directions is obtained by the following [Equation 1]. (201).

In the second step, using the h and v values obtained in the first step, the contour intensity I and the direction θ of the pixel P0 are obtained by the following Equation 2 (202).

The extracted direction θ has a value of −90 degrees to 90 degrees, but this angle is divided into 15 directions to reduce the amount of data. Here, the number 15 is excluding the number (typically expressed as 0) for indicating the case where the characteristic as an outline is not clear among the 16 directions that can be represented by 4 bits. Thus, the direction outline map of the present invention is 4 bits. The strength and directivity of the contours in the grid can be expressed simultaneously.

In the third step, the representative value of the grid is set (203). After extraction of the contour pixels by the above method, each pixel has intensity information as the contour and directional information indicating the direction. With this as the basic data, the feature extraction means of the present invention divides the entire image into a grid of a certain size, and sets the representative value of the grid by analyzing the above characteristics of the pixels included in each grid. The table in which representative values are set for each grid is called a direction outline map. A method of generating such a direction contour map will be described with reference to FIG. 4.

First, the count and histogram for the number of pixels are initialized (Count: = 0, Hist [i]: 0) 401, and a check is made that the intensity information I (p) of the outline pixel is larger than a predetermined value Th _i . (402). If the result of the inspection indicates that the intensity information of the contour pixel is larger than a predetermined value, the count is increased (Count: = Count + 1), and the histogram of the direction value of the pixel in each grating is increased by one (Hist [θ (p)]). : = Hist [θ (p)] + 1) (403). At this time, when the intensity information of the outline pixel is smaller than a predetermined value, the count and histogram are not increased. This is because, when the intensity of the outline pixel is weak, there is almost no characteristic as an outline, so the directionality also has no meaning. This process is repeated for every pixel in the grid (404). Thereafter, the number of pixels Count included in the histogram is checked to be less than the threshold value Tn (405). 406). Grids with a representative value of 0 are excluded from the comparison. In this way, the strength and direction information of the contour can be simultaneously expressed by resetting the direction information of the table for the portion where the characteristic of the contour is not clear. On the other hand, when the number of pixels Count included in the histogram is greater than or equal to the threshold value Tn, the largest value of the histogram, that is, the direction of the largest number of pixels, is set as a representative value of the grid (407).

In this way, a table in which representative values are set for each grid is referred to as a directional contour map, and the directional contour map is recorded by the storage means, so that it can be used as a feature amount representing an image when performing a search later. In this case, the storage means may be stored in a database or stored in a separate file according to the configuration of the system.

As described above, the direction outline map stored for each image may be used to search for similar images using the search means shown in FIG.

The search process consists of two steps. In the first search, a search is performed using the number of grids whose direction value is set to 0 in the direction contour map. In general, in the case of an image having sharp contrast, the intensity of the outline is strong, and otherwise, the intensity of the outline tends to be weakened. Therefore, by using the number of grids whose direction value is set to 0, it is possible to compare the overall characteristics of such images. This first search has the advantage that it can be performed at high speed because it ends with a simple comparison of numbers.

The second search is performed on the image that passed the first search as follows.

For all the grids in which the stored direction contour map Mr and the query direction contour map Mq are compared, the difference d of the direction values is obtained as shown in Equation 3 below.

d = | Mr-Mq |

if (d> = 8) d = 14-8

The difference (d) of the direction values calculated as above is calculated and added to all the grids. At this time, however, if either of the direction outline maps Mr and the query direction outline maps Mq is 0, the direction is excluded from the calculation target.

Finally, a value obtained by dividing the sum D of the value D by the calculated number N of grids is regarded as a difference value between Mr and Mq, and when the value is small, a similar image is determined.

The present invention described above is capable of various substitutions, modifications, and changes without departing from the technical spirit of the present invention for those skilled in the art to which the present invention pertains. It is not limited.

As described above, according to the present invention, by extracting the information related to the contour from the still image and the moving picture, it is possible to approximate the object included in the image. It is possible to search for near images and improve the quality of image database search.

Claims (5)

Image input process of reading digitized still images and videos, A feature extraction process of analyzing a content of the input image to create a direction contour map; A storing process for storing the created direction contour map; And retrieving the desired data by verifying the similarity of the directional contour maps. The method of claim 1, The feature extraction process may include performing mask processing on all pixels on the bitmap stored in the memory to obtain a difference between pixel values in the horizontal and vertical directions; Obtaining contour intensity and direction of the pixel by using the difference between the pixel values in the horizontal and vertical directions; Dividing the entire image into a grid having a constant size using the contour intensity and direction information of the pixels as basic data, analyzing the characteristics of the pixels included in each grid, and setting a representative value of the grid to create a direction contour map. Image retrieval method using a direction contour map comprising a. The method of claim 2, The method of generating a direction contour map by setting the representative value of the grid includes: initializing a count and histogram for the number of pixels; If the intensity information of the outline pixel is greater than a certain value, if the intensity information of the outline pixel is greater than a certain value, the count is increased, a histogram of the direction value of the pixel in each grid is obtained, and the intensity information of the outline pixel is a constant value. If less, do not increase the count and histogram, If the number of pixels included in the histogram is less than the threshold, the direction information of the table is reset. If the number of pixels included in the histogram is greater than or equal to the threshold, the largest value of the histograms is set as the representative value of the grid. Image retrieval method using a direction contour map comprising the step of. The method of claim 1, The searching process may include performing a search based on the number of grids in which the direction information is reset in the direction contour map and performing comparison based on the overall characteristics of the image; The difference in the direction values is obtained for all the grids comparing the stored direction contour map and the query direction contour map, the difference in the direction values is added to all the grids, and the sum of the direction difference differences is divided by the number of grids. And defining a value as a difference value between the direction contour map and the query direction contour map, and determining the value as a similar image when the value is small. Image input process of reading digitized still images and videos, A feature extraction process of analyzing a content of the input image to create a direction contour map; A storing process for storing the created direction contour map; A computer-readable recording medium having recorded thereon a program for executing a searching process for searching for desired data by verifying similarity of the directional contour map.