Color texture feature extraction method based on quaternion gabor filter

Abstract

The invention belongs to the technical field of image processing, and in particular relates to a color texture feature extraction method based on quaternion Gabor filtering. According to the quaternion and Gabor filter, the quaternion Gabor filter is deduced, the original color image to be extracted is input, and the original color image is processed by the quaternion Gabor filter convolution algorithm to obtain the color texture feature image. Several pieces of color texture feature images with high similarity of the original color images, extracting the Tamura features of each channel of the several pieces of color texture feature images; The Tamura features of each channel form a set of feature vectors together, that is, the color texture feature vector is obtained. The method of the invention can largely retain texture features such as roughness, contrast and directionality of the original image, and can extract color information of the original image at the same time.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a color texture feature extraction method based on quaternion Gabor filtering. Background technique [0002] Texture is an important visual clue of features, and an important but difficult to describe feature in image processing. Up to now, there is still no recognized and strict definition of image texture features. The research content of texture analysis mainly includes texture classification and segmentation, texture synthesis, texture retrieval and texture restoration shape. One of the most basic problems in these research contents is texture feature extraction. The quality of extracted texture features directly affects the segmentation and classification results. The existing texture feature extraction methods mainly include statistical methods, model methods, signal processing methods and structural methods. Among them, the Gabor filter in the signal ...

AI Technical Summary

Problems solved by technology

However, the existing mature texture feature extraction methods only stay in the texture feature extraction of grayscale images, ignoring the color features of the image, which will have a greater impact on image classification and segmentation

[0003] Some researchers have proposed a color texture segmentation algorithm using a reduced double quaternion. For example, a color texture segmentation algorithm using a reduced double quaternion has proposed digital features of an image, such as mean value and variance; but this algorithm also has the following disadvantages: On the one hand, the color texture feature image is not provided, and on the other hand, the color feature of the extracted texture image is not used

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