Contour Integration and Segmentation with a New Lateral Connections Model

摘要

Automatically target contour detection from cluttered scenes is a very difficult task for computer vision. Humans, however, have a much better background suppress ability. The preceding models could not implement such a task very well. In this letter, an effective contour integration method based on human visual perception mechanism is proposed. The algorithm combines the properties of primary visual cortex and psychology researching results to simulate the contour perception of the V1 cortex. The new lateral connection based computational model have a better texture suppress ability, while, target’s contour is enhanced. Compared with traditional methods, experiments show that the new method implement a more reasonable simulation of the V1 function structure, availably enhance the target’s contour while suppress the cluttered background, obtain a balance between over and lose detection, besides, it has better accuracy with less computational complexity and time-consuming.