Contour and boundary detection algorithm based on visual color theory and homogeneity inhibition

A boundary detection and color technology, applied in computing, image data processing, image analysis, etc., can solve time-consuming problems

Inactive Publication Date: 2016-12-14
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

The probabilistic contour detection algorithm has achieved good results, but the algorithm is time-consuming due to the calculation of three gradi

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  • Contour and boundary detection algorithm based on visual color theory and homogeneity inhibition
  • Contour and boundary detection algorithm based on visual color theory and homogeneity inhibition
  • Contour and boundary detection algorithm based on visual color theory and homogeneity inhibition

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[0202] Below to Figure 8 The shown image is taken as an example to further describe the present invention in detail. The present invention will be further described below in conjunction with the accompanying drawings and embodiments. The present invention mainly comprises the following steps: processing of cone cells, processing of ganglion / lateral geniculate body, processing of V1 area of ​​visual cortex, homogeneous inhibition, contour detection model based on visual color theory and homogeneous processing, post-processing deal with.

[0203] (1) Processing of cone cells

[0204] The input image stimulus is first divided into three color channels by cone cells: red, green, and blue color channels, which are represented by R(x,y), G(x,y), and B(x,y) respectively. The construction of the yellow channel Y(x,y) based on the theory of three primary colors can be expressed by the following expression:

[0205] Y(x,y)=(R(x,y)+G(x,y)) / 2

[0206] Assuming that the input image i...

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Abstract

The invention discloses a contour and boundary detection algorithm based on a visual color theory and homogeneity inhibition, belongs to the cross field of computer vision and pattern recognition, and aims at extracting the contour and boundary of a target from a complex natural scene. Through the research of the visual information processing mechanism of human eyes, the method carries out the mathematic modeling of a receptive field of a nerve cell of a visual pathway at each stage, and employs the modulation effect of a non-classical receptive field to inhibit the texture edge, thereby highlighting the contour and boundary. The innovation of the invention lies in introducing the visual information processing mechanism of human eyes to a contour and boundary detection model, detecting the color and brightness boundary through setting imbalance vision cone input, maintaining the contour integrity, giving consideration to the homogeneity of the texture region and the homogeneity inhibition on a classical receptive field from the non-classical receptive field, employing the homogeneity inhibition to inhibit the texture edge, and extracting the contour and boundary of a natural image.

Description

technical field [0001] The invention belongs to the intersection field of image processing, computer vision and pattern recognition, and specifically relates to a contour and boundary detection algorithm based on visual color theory and homogeneity suppression. Background technique [0002] Contour and boundary detection is a basic topic in the fields of image processing, computer vision, pattern recognition, etc. The quality of the detection results directly affects more advanced visual tasks. Contour and boundary detection can be used in target recognition, object tracking, image segmentation and other fields. important research significance. [0003] Traditional edge detection operators often detect edges based on sudden changes in low-level information such as color and brightness. Because only low-level information is used, contours and texture edges cannot be effectively distinguished, so the detection results contain more unnecessary texture information. The probabil...

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Application Information

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IPC IPC(8): G06T7/00
Inventor 邹腊梅李鹏杨卫东曹治国高亚红万敏罗鸣金留嘉
Owner HUAZHONG UNIV OF SCI & TECH
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