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Image classification method based on improving sparse constraint bilinear model

A sparse constraint and classification method technology, applied in the field of image processing, can solve problems such as unavailable division and unfavorable classification, and achieve high classification performance, performance improvement and robustness

Active Publication Date: 2014-03-26
INST OF AUTOMATION CHINESE ACAD OF SCI
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  • Application Information

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Problems solved by technology

However, the method of dividing the pyramid by this method is empirical, and the most effective division cannot be obtained in advance.
On the other hand, the impact of each visual word on classification performance is different, and giving each visual word the same weight is not conducive to the final classification

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  • Image classification method based on improving sparse constraint bilinear model
  • Image classification method based on improving sparse constraint bilinear model
  • Image classification method based on improving sparse constraint bilinear model

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Embodiment Construction

[0021] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the following further describes the present invention in detail in conjunction with specific embodiments and with reference to the accompanying drawings.

[0022] The present invention uses image block and sparse constraints to propose an effective image classification method. figure 1 It shows that the system of the present invention improves the sparse constrained bilinear model for image classification framework, including image local feature extraction, component-based image representation, promoted sparse constrained bilinear model, and image classification.

[0023] The present invention mainly includes two parts: component-based image representation and lifting sparse constrained bilinear model.

[0024] (1) Image representation based on components:

[0025] The image representation part adopts component-based representation, figure 2 Shows a description of a component-...

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Abstract

The invention provides an image classification method based on improving a sparse constraint bilinear model, comprising the following image classification steps: S1. extracting the local characteristic of the image from the image; S2. intensively extracting a plurality of parts from the image; S3. taking the histogram of a virtual word as the character representation of each part, arranging the character representation of each part in sequence, and representing the image in a matrix mode; and S4. improving the relationship between an analog visual word to parts and parts to image classification of the sparse constraint bilinear model to realize the purpose of image classification. In order to improve the distinguishing capability of the method, sparse constraint is added, and the robustness of the method is improved by a promotion strategy. The experiment results on three databases prove the effectiveness of the method.

Description

Technical field [0001] The invention belongs to the field of image processing, and relates to an image classification method based on a lifting sparse constraint bilinear model. Background technique [0002] With the explosive growth of multimedia data, it is more and more difficult to manually classify images, and automatic classification based on image content is getting more and more attention. Automatic image classification technology can predict the category of the image by processing and analyzing the content of the image itself, avoiding a lot of manual processing. However, due to the different shapes of various objects in the image, the location is not fixed, and there may be occlusion, automatically learning a robust image feature representation and prediction model is still a very challenging problem. [0003] Most traditional image classification methods are based on the bag-of-words model. This method first extracts local features on the image, quantizes the local fea...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
Inventor 卢汉清刘静张淳杰
Owner INST OF AUTOMATION CHINESE ACAD OF SCI