Target contour detection method of biomimetic jumping eye movement information processing mechanism

Abstract

The invention aims at providing a target contour detection method of a biomimetic jumping eye movement information processing mechanism. The method comprises the following steps that a to-be-detected image subjected to grey processing is input; Gabor filtering in all the directions is carried out, and a maximum value diagram of the to-be-detected image is obtained; an initial DoG template is set up and converted, the maximum value diagram is filtered through all converted DoG templates, and conversion filtering result values of all pixel points are obtained; the conversion filtering result values of all the pixel points are corrected, and a correction restraining diagram is obtained; the filtering result values of corresponding pixel points, in the same direction with all pixel points in the Gabor energy diagrams, in the corrected maximum restraining value diagram are subtracted from the Gabor energy values of all the pixel points, in all the directions, in the Gabor energy diagram, the results are adopted as the contour values of the pixel points, the contour values are processed through non-maximum value restraining and dual threshold values, and a final contour diagram is obtained. According to the detection method, the defects that in the prior art, the biofidelity is low and the contour recognition rate is low are overcome, and the advantages of being high in biofidelity and contour recognition rate are achieved.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method for detecting the outline of a target imitating a biological saccade eye movement information processing mechanism. Background technique [0002] Contour detection is an important part of image processing and computer vision. Correctly detecting object contours from complex backgrounds is a very important and difficult task. Among many traditional image processing methods, Canny operator, active contour model, etc. are more successfully applied to contour detection. These methods mainly use the brightness difference information in the image for detection, and cannot distinguish the target contour from other cluttered boundaries. Therefore, it is difficult for these methods to obtain satisfactory results when the contrast changes in the image are relatively large and the background interference is relatively large; [0003] The further optimization scheme of the prior a...

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Problems solved by technology

[0004] The present invention aims to provide a target contour detection method imitating the information processing mechanism of biological hopping eye movement, which overcomes the defects of low simulation degree and low contour recognition rate in the prior art, and has the characteristics of high simulation degree and high contour recognition rate

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