计算机工程与应用2017，Vol.53Issue(24)：142-146,5.DOI:10.3778/j.issn.1002-8331.1612-0186
一种脑启发式的边缘检测模型
Brain-inspired edge detection model
摘要
Abstract
Edge is a basis feature of object recognition. Traditional edge detection methods have some limitations. In view of the fact that human visual system can perceive edge information of the object with high efficiency and accuracy, according to the receptive fields of Lateral Geniculate Nucleus(LGN)and simple cells in primary visual cortex(V1), a brain-inspired Feedforward LGN-V1(FLV)model for visual perception is put forward. Firstly, the concentric receptive fields of a LGN cell is simulated by the difference of Gaussian function, then, cell groups are constructed by the union of LGN cells with the same polarity, and a V1 simple cell with a certain preferred orientation is achieved by combining two parallel sets of co-linear cell groups. Finally, the responses of all V1 simple cells are obtained by integration of responses of different simple cells. Test results show that the FLV model reflects the properties of real simple cells well. Compared with the traditional methods, the proposed model is more effective and has better robustness in edge detection.关键词
边缘检测/人类视觉系统/侧膝体/初级视皮层/感受野Key words
edge detection/human visual system/Lateral Geniculate Nucleus(LGN)/primary visual cortex(V1)/recep-tive field分类
信息技术与安全科学引用本文复制引用
吕超,许悦雷,李帅,马时平,辛鹏..一种脑启发式的边缘检测模型[J].计算机工程与应用,2017,53(24):142-146,5.基金项目
国家自然科学基金(No.61372167,No.61379104). （No.61372167,No.61379104）
