Image color retrieval method and system

Abstract

The invention discloses an image color retrieval method and an image color retrieval system and relates to the field of image processing. The method comprises the steps of performing quantification processing to HSV (Hue, Saturation and Value) color spaces of pixels in an image to obtain quantified color values within a range of 0 to N, wherein non-uniform fuzzy quantification is performed to tone values; statistically collecting a histogram of the quantified color values of the pixel of the image and performing normalization processing by using the sum of the pixels of the image to obtain a color characteristic vector of the image; comparing the color characteristic vector of the image to the color characteristic vectors of other images to determine the similarity of the images. The method and the system disclosed by the invention have the advantages that since images related to the inquired image color are extracted from a database by taking the color characteristic vector after image quantification as a relevant judgment basis, the image retrieval is enabled to be more intelligent and the extraction result of color-related images becomes more accurate; since the images in the database are processed in advance by adopting an offline module, the execution speed is effectively improved.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image color retrieval method and system. Background technique [0002] With the rapid development of multimedia technology, digital imaging technology and computer technology applications, as well as the popularization and application of large-capacity storage devices and digital devices, image and video data show a geometric increasing trend. At the same time, large-capacity image / video databases have emerged . However, digital imaging equipment itself does not have image database management and query functions. How to quickly and accurately find the desired digital image from the vast image database has become one of the hot spots in multimedia technology research in recent years. The research on image retrieval technology has provided strong support to multiple research fields such as multimedia digital library, trademark copyright management and satellite remote ...

AI Technical Summary

Problems solved by technology

However, this image retrieval method has the following shortcomings that are difficult to overcome: 1) The method of manual annotation is very subjective, and different people may have different interpretations of the same image, and the same description vocabulary may also There are many different meanings, and it is difficult for different countries and different nationalities to explain the images in a unified language

2) Due to the expansion of data scale, the overhead of manual labeling is becoming more and more unbearable

3) The content of the image is relatively rich and has the characteristics of "a picture with a thousand characters". In some cases, it is impossible to clearly express the meaning expressed by the image itself with limited words, especially when the image contains some deep meaning.

4) Although many parameter information such as the creation date, format information, and resolution of the image can be automatically extracted to a certain extent, and provide some basic index clues, the method based on text content annotation is not as good as the similarity of image visual features. Difficult to search

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