Method for fusing significant structure and relevant structure of characteristics of image

A technology of image features and related structures, applied in image enhancement, image data processing, instruments, etc., can solve the problem of difficult fusion of multi-featured salient structures and related structures in images

Active Publication Date: 2014-07-02
XIAN UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a fusion method of salient structures and related structures of image features, which solves the problem in the prior art that it is difficult to fuse the salient structures and related structures of multi-featured images, and finally obtains structural fusion features with strong discrimination ability

Method used

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  • Method for fusing significant structure and relevant structure of characteristics of image

Examples

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Embodiment 1

[0079] In Example 1, the Columbia target image library COIL20 contains 1440 images taken from 20 targets at different angles. Each image has a pixel size of 32×32 and has 256 gray levels. The fusion method of the salient structure of the image feature and the related structure of the present invention is used for the image in the image library, and finally the fusion feature is obtained. The experimental strategies of nearest neighbor classifier and leave-one-out method are used to classify images in this image library. Table 1 shows the image recognition rates obtained by different methods. CCA is a canonical correlation analysis method.

[0080] Table 1 The recognition rate of different methods in COIL20 library

[0081] Method

Embodiment 2

[0082] In Embodiment 2, the ORL face database contains 400 face images from 40 people, and each image has 32×32 pixels and 256 gray levels. The fusion method of the salient structure of the image feature and the related structure of the present invention is used for the image in the image library, and finally the fusion feature is obtained. The experimental strategies of nearest neighbor classifier and leave-one-out method are used to classify images in this image library. Table 2 shows the recognition rates obtained in experiments of different methods. CCA is a canonical correlation analysis method.

[0083] Table 2 The recognition rate of different methods in ORL library

[0084] Method

[0085] It can be seen from Table 1 and Table 2 that the recognition rate of the image obtained by the method of fusing the significant structure of the image feature and the related structure of the present invention is higher than that of the image obtained by other methods.

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Abstract

The invention discloses a method for fusing a significant structure and a relevant structure of the characteristics of an image. The method for fusing the significant structure and the relevant structure of the characteristics of the image comprises the steps of extracting the HOG characteristic and the LBP characteristic of the image, measuring the significant structure of the image characteristics inside sample sets, measuring the relevant structure of the image characteristics between the sample sets, and conducting fusion and mapping of the significant structure and the relevant structure. According to the method for fusing the significant structure and the relevant structure of the characteristics of the image, the HOG characteristic and the LBP characteristic of the image are extracted firstly, the significant structure of the image characteristics inside the sample sets is measured through x<2> measurement, the relevant structure of the image characteristics between the sample sets is measured through canonical correlation, and finally the structures are fused through a matrix spectrum optimization solution method, so that a fused characteristic set is obtained. By the adoption of the method for fusing the significant structure and the relevant structure of the characteristics of the image, the problem that in the prior art, the significant structure and the relevant structure of the multiple characteristics of the image can not be fused is solved, and structural fusion characteristics high in discrimination capacity are obtained.

Description

Technical field [0001] The invention belongs to the technical field of video surveillance image processing methods, and relates to a method for fusing the prominent structure of image HOG features and LBP features and related structures. Background technique [0002] In recent years, there have been more and more applications of intelligent monitoring systems based on content analysis. To intelligently analyze and identify targets, image description and cognition are important problems to be solved because of the diversity of image description and the diversity of multi-feature structure observations. It is difficult to completely describe the essential structure of the image with a single observation and multi-feature structure. The prior art cannot perform the fusion of the significant structure and related structure of the image with multiple features, and thus cannot more accurately characterize the image features. Summary of the invention [0003] The purpose of the present ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/50
Inventor 蔺广逢缪亚林陈万军陈亚军张二虎朱虹
Owner XIAN UNIV OF TECH
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