Contour detection method based on classic receptive field fixation micro-motion mechanism

Abstract

The invention aims to provide a contour detection method based on a classic receptive field fixation micro-motion mechanism, and the method comprises the following steps: A, inputting a to-be-detectedimage obtained through gray processing, presetting a Gaussian function of a plurality of scale parameters, and obtaining the Gaussian filtering response of each scale parameter of each pixel point through calculation; b, calculating and obtaining a plurality of annular Gaussian first-order derivative functions in one-to-one correspondence with the plurality of scale parameters; c, for each pixelpoint, calculating and obtaining a micro-motion fusion response of each direction parameter of the pixel point; d, for each pixel point, taking the maximum value from the micro-motion fusion responseof each direction parameter of the pixel point as the classic receptive field response of the pixel point; e, presetting a distance weight function and an inhibition coefficient, and calculating inhibition response of each pixel point; and F, subtracting the suppression response of the pixel point from the classical receptive field response of each pixel point to obtain a final contour map. The contour detection method overcomes the defects in the prior art, and has the characteristics of strong simulation and high detection accuracy.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a contour detection method based on a classic receptive field fixation micro-movement mechanism. Background technique [0002] Contour detection is a basic task in the field of computer vision. Unlike edges, which are defined as strong brightness changes, contours usually represent the boundaries of one object to other objects. Contour detection models inspired by biology are currently one of the mainstream research directions, but most of them simply simulate a part of the physiological characteristics of the visual system, and the lack of research on the role of the fixation micro-movement mechanism in contour detection has caused a certain degree of Due to the lack of upper contour information and the enhancement of texture information, the integrity of the target contour cannot be well guaranteed. The few schemes that consider the physiological mechanism of fixation fretting ...

AI Technical Summary

Problems solved by technology

Contour detection models inspired by biology are currently one of the mainstream research directions, but most of them simply simulate a part of the physiological characteristics of the visual system, and the lack of research on the role of the fixation micro-movement mechanism in contour detection has caused a certain degree of The lack of upper contour information and the enhancement of texture information can not guarantee the integrity of the target contour.

However, the few schemes that consider the physiological mechanism of fixation fretting focus on the effect of texture suppression in the non-classical receptive field area, while ignoring the application in the classical receptive field area of ​​visual cells.

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