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.

Key words: edge detection, human visual system, Lateral Geniculate Nucleus（LGN）, primary visual cortex（V1）, receptive field

摘要： 边缘是物体的基础特征，传统边缘检测方法具有一定的局限性。鉴于人类视觉系统能高效准确地感知物体的边缘信息，根据大脑侧膝体（Lateral Geniculate Nucleus，LGN）和初级视皮层（primary visual cortex，V1）简单细胞的感受野特性，提出一种脑启发式的前馈LGN-V1（Feedforward LGN-V1，FLV）视觉感知模型。首先用高斯函数之差模拟单个LGN细胞的同心圆式感受野，再通过同类LGN细胞的联合构建细胞组，最后将两类细胞组分别共线排列并平行放置模拟得到特定偏好朝向V1简单细胞。通过多简单细胞响应的整合获取全体V1简单细胞的响应。实验结果表明，FLV模型能体现真实简单细胞的生物特性。较传统的边缘检测方法而言，所提模型效果更优，具有更好的鲁棒性。

关键词: 边缘检测, 人类视觉系统, 侧膝体, 初级视皮层, 感受野