A method and device for image recognition

Abstract

The embodiment of the present invention discloses an image recognition method and device. The method includes: acquiring feature vectors containing spatial information of N image features and L scales according to the original image. Among the L scales, the sub-regions are divided up and down Mainly, to obtain the feature vector of each sub-region based on the N image features, obtain the first histogram weight of the block histogram of the L scales, the weight of the central sub-region of the connection histogram has been increased by Reduce the impact of the environment; connect the histograms of each scale based on the first histogram weight to obtain the concatenation histogram of the block histograms of the L scales, and obtain the individual histograms of each scale based on the concatenation histogram. The N image features of the sub-region; using the feature vectors to classify and identify the original image. In this way, the spatial orientation information of the image can be reflected and the environmental impact can be reduced.

Description

Technical field [0001] The invention relates to the field of artificial intelligence, in particular to an image recognition method and device. Background technique [0002] With the development of image processing technology, more and more fields have begun to use image processing technology. For example, in the industrial field, image recognition industrial components have begun to replace the previous methods of manually identifying industrial components. [0003] Clothing recognition refers to the use of image processing technology to recognize the color and pattern of clothing, so that the color and style of clothing can be further recognized, and it can be combined with face recognition to improve the accuracy of face recognition. At present, when using image technology to recognize images, they often use Bag of Features (BOF) or Pyramid Model (Spatial Pyramid Matching, SPM) to extract image features, and then recognize the image, but based on the BOF model The spatial struct...

AI Technical Summary

Problems solved by technology

At present, when using image technology to recognize images, Bag of Features (BOF for short) or Spatial Pyramid Matching (SPM for short) is often used to extract the features of the image, and then the image is recognized, but based on the BOF model The spatial structure information of the image is lost in the extracted features and the SPM model adopts a uniform division method, which is not suitable for clothing recognition with rich poses and angles. At the same time, the entire image has the same proportion of features, which cannot effectively reduce the background. Influence, so that the accuracy of image recognition is low

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