Contour Detection Model Based on Mechanisms of Visual Perception in Environment of Low Contrast
CHEN Jian-Jun, REN Yong-Feng, ZHENG Guo-Yong
National Key Laboratory for Electronic Measurement Technology,North University of China,Taiyuan 030051 Key Laboratory of Instrumentation Science and Dynamic Measurement,Ministry of Education, North University of China,Taiyuan 030051
Abstract：The traditional contour detection model based on mechanisms of visual perception loses some of the object contours at low local contrast. And it augments the noise or breaks around the corner of the local high curvature contour in the collinear enhancement. To solve these problems, a contour detection model based on the mechanism of visual perception in the environment of low contrast is proposed. Based on the traditional model, the adjustment mechanism of stimulus contrast is introduced, which adjusts the size of receptive field and the strength of lateral inhibition. According to Gestalt principles of perceptual organization, the disinhibition region is divided into adjacent disinhibition region and peripheral disinhibition region which are given different enhancement mechanisms respectively. And the acquired binary image is morphologically filtered to eliminate noises. The experimental results for natural images show that the model has significant effects on above issues and it improves the performance of contour extraction in natural background.
陈建军，任勇峰，甄国涌. 引入低对比度环境下视觉感知机制的轮廓检测模型[J]. 模式识别与人工智能, 2012, 25(5): 845-850.
CHEN Jian-Jun, REN Yong-Feng, ZHENG Guo-Yong. Contour Detection Model Based on Mechanisms of Visual Perception in Environment of Low Contrast. , 2012, 25(5): 845-850.
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2012, Vol. 25 
