Image classification method based on category correlated codebook and classifier voting strategy

Abstract

The invention discloses an image classification method based on a category correlated codebook and a classifier voting strategy. The method comprises the following steps of: expressing an image as a set of local salient region image blocks by an image data set pre-processing module; generating category correlated codebooks by a category correlated codebook generating module; expressing the image as an image vector by an image vectoring module, and training a classifier between two random categories by selecting the trained image vector and a category tag corresponding to the trained image through a category correlated classifier training module; and finally, determining the category tag of the tested image according to voting results by a classifier-voting-strategy-based tested image classifying module. The category correlated codebook generating module effectively solves the contradiction of dimension disaster caused by over large codebooks and judgment insufficiency caused by over small codebooks; and meanwhile, the category correlated classifier training module also gets rid of the problems caused by sample unbalance in multi-category classification, and the classification performance is improved.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition and information processing, and relates to an image classification method based on category-related codebooks and classifier voting strategies, in particular to an image classification method. Background technique [0002] Due to the low price of digital products such as digital cameras, image and video data can be easily captured and stored in an electronic form that is convenient for computer processing. At the same time, the rapid development of Internet resources makes the majority of users begin to face a huge data resource. It has become unrealistic to simply use manpower to maintain and organize these data. Therefore, developing a technology to effectively organize these personal or corporate image and video data has become a hot issue. However, computers cannot "see" very clearly: they cannot convert the color pixels in an image into a higher-level semantic representation lik...

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Problems solved by technology

[0006] In order to solve the difficulties existing in the multi-category classification problem in the prior art, the purpose of the present invention is to be able to gather discriminative local salient area image blocks between categories as a codebook, and to effectively reduce the dimensionality of image representation in classification The solution to the disaster problem, for this reason, the present invention provides a kind of image classification method based on category-related codebook and classifier voting strategy

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