2 December 2011 Contour integration and segmentation with a new lateral connections model
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Proceedings Volume 8004, MIPPR 2011: Pattern Recognition and Computer Vision; 800415 (2011) https://doi.org/10.1117/12.902140
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China
Abstract
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.
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Chao Cai, "Contour integration and segmentation with a new lateral connections model", Proc. SPIE 8004, MIPPR 2011: Pattern Recognition and Computer Vision, 800415 (2 December 2011); doi: 10.1117/12.902140; https://doi.org/10.1117/12.902140
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