高技术通讯2024，Vol.34Issue(1)：15-24,10.DOI:10.3772/j.issn.1002-0470.2024.01.002
基于双通路视觉系统的自适应轮廓检测模型
Adaptive contour detection model based on dual-pathway visual system
摘要
Abstract
In this paper,an adaptive contour detection model based on dual-pathway visual system is proposed to solve the problem of incomplete contour extraction due to the interference of background texture.First,the information acquisition and evaluation process of the subcortical pathway is used to evaluate the saliency of the image as a whole,so as to obtain the probability distribution of contour information.Then,the dynamic properties of the re-ceptive field in the classical visual pathway are simulated using adaptively scaled Gaussian derivative functions to enhance the capture of contour details by the model.Finally,based on the surround inhibition algorithm,the spar-sity of all edges is measured in conjunction with the spatial distribution of pixels,which allows for a more accurate distinction between contour and texture edges.The experimental results show that the model proposed in this paper can effectively inhibit the background texture,improve the contour continuity,and have better contour detection performance.关键词
轮廓检测/视觉机制/显著评估/感受野/稀疏度量Key words
contour detection/visual mechanism/saliency evaluation/receptive field/sparsity measurement引用本文复制引用
王宪保,陈斌,项圣,陈德富,姚明海..基于双通路视觉系统的自适应轮廓检测模型[J].高技术通讯,2024,34(1):15-24,10.基金项目
①国家自然科学基金(61871350)和浙江省基础公益研究计划(LGG19F030011)资助项目. （61871350）
