关键词: 初级视皮层, 细胞模型, 边缘检测, 时空滤波器, 感受野, 生物视觉

Abstract: As for balancing the accuracy of edge detection and the difficulty of anti-noise performance, and referring to the dynamic and static perceptions of the primary Visual cortex（V1） cells, this paper proposes an orientation selectivity V1 model which is applied to image edge detection. Spatio temporal filters are adopted to simulate the receptive fields of the V1 simple cell. The response of simple cells is obtained by using the energy model and normalization to get the V1 cells model. Thus the natural image edge is detected by using static perception of V1 cells. Simulation results show that the V1 model can basically fit the biological data and has the universality of biology. What’s more, compared with the traditional edge detection operators, the proposed model is more effective and has better robustness. Based on the biological experimental results, this paper constructs a biological vision model and applies it to image processing, which makes a helpful exploration to the fusion of biological vision and computer vision.

Key words: primary visual cortex, cell model, edge detection, spatiotemporal filter, receptive field, biological vision