Method and device for extracting image features

Abstract

The embodiment of the invention provides a method for extracting image features. The method comprises the steps of calculating HOG feature information corresponding to each block structure in a target image, wherein each block structure comprises a pixel matrix formed by a preset number of pixel values; in allusion to each block structure, generating an input set of a PCA algorithm according to the pixel matrix in the block structure; calculating PCA feature information corresponding to each block structure by using the PCA algorithm; cascading the HOG feature information and the PCA feature information corresponding to each block structure, and generating new HOGP feature information corresponding to each block structure; and cascading the new HOGP feature information corresponding to all block structures, and generating new HOGP feature information of the target image. Rich image features containing detail features and contour features can be extracted by applying the embodiment of the invention.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a method and device for extracting image features. Background technique [0002] With the rapid development of image recognition technology, the accuracy of image recognition in various application fields is getting higher and higher. In order to improve the accuracy of machine recognition of images, people use image feature visualization methods to improve the image recognition algorithms used by machines in image recognition. [0003] Image feature visualization specifically refers to restoring the target image according to the image features of the target image extracted by the machine. In this way, the image recognition algorithm can be improved according to the difference between the original target image and the restored target image. If the difference between the original target image and the restored target image is small and the similarity is high, it means tha...

AI Technical Summary

Problems solved by technology

[0004] At present, in the process of image feature visualization, image recognition algorithms for extracting image features include principal component analysis (Principal Component Analysis, PCA) algorithm and feature detection (Histogram of OrientedGridients, HOG) algorithm; among them, PCA algorithm is good at extracting image However, for images with less detailed features, such as sky, sea, wall, etc., the image information contained in the extracted PCA feature information is incomplete; while the HOG algorithm is good at extracting the contour features of the image, but the extracted HOG feature information ignores the detailed information of the image

In this way, according to the image features extracted using the PCA algorithm or the HOG algorithm, the restored image has a large difference and a low similarity with the original target image.

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