Visual word bag feature weighting method and system based on classification drive

Abstract

The invention discloses a visual word bag feature weighting method and system based on classification drive. The method comprises the steps that images are downloaded from the Internet, and an image database is established; the visual word bag features of all N images in the image database are extracted; the reverse index of the visual word bag features of all N images is established; N1 images and corresponding visual word bag features are extracted randomly from the image database; the N1 images are made to form C visual classes through a clustering algorithm; images are chosen randomly from each visual class to form a study sample set of the visual class; a weighting study sample set of the visual word bag features is established on the study sample set of the visual class for each visual class; the weighting study sample sets are used for training the visual classes to form supporting vector machine judging modules of the visual classes. The visual word bag feature weighting method and system based on classification drive can solve the technical problems that index precision is low, and the difference among different searching images can not be excavated in an existing method.

Description

technical field [0001] The invention belongs to the field of content-based image retrieval, and more particularly relates to a classification-driven visual bag-of-words feature weighting method and system. Background technique [0002] The content-based image retrieval technology extracts the underlying feature vectors according to the image content, and represents the similarity between images by calculating the similarity between image feature vectors. Mainstream image retrieval systems use local features to describe image content. Local features have good invariance, and cover more information, and can handle more complex object occlusion, illumination changes and other situations. However, in the process of image retrieval based on local features, the calculation of similarity between local feature sets involves matching between local features, which requires a large amount of calculation and cannot meet the needs of real-time image retrieval. In order to reduce the co...

AI Technical Summary

Problems solved by technology

[0006] In view of the above defects or improvement needs of the prior art, the present invention provides a classification-driven visual bag-of-words feature weighting method and system, the purpose of which is to solve the problems of low retrieval accuracy and inability to mine different query images technical issues

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