基于初级视通路视觉感知机制的轮廓检测方法

考虑到初级视通路中视觉信息传递和处理过程中的特点,本文提出了一种基于视觉感知机制的轮廓检测新方法.构建视觉信息局部细节检测与整体轮廓感知的不同路径.利用高斯导函数提取初级轮廓响应;构建神经网络,利用时空编码提高主体轮廓对比度;然后,利用非经典感受野的侧抑制作用抑制纹理背景;另外,针对轮廓信息强化以及检测鲁棒性的要求,在视辐射区提出了一种信息冗余度增强编码机制;最后,将初级轮廓直接前馈至初级视皮层,以达到轮廓响应的快速调节和完整性融合.以RuG40图库为实验对象,经过非极大值抑制和阈值处理,得到的轮廓二值图与基准轮廓图比较,在整个数据集中的最优平均P指标和每张图的最优平均P指标分别为0.48和0.55,并且FPS达到了1/2.结果表明本文方法能有效突出主体轮廓并抑制纹理背景,为后续图像理解和分析提供了一种新的思路.

A Contour Detection Method Based on Visual Perception Mechanism in Primary Visual Pathway

A new method of contour detection is proposed in this paper according to the characteristics of visual information transmission and processing which is based on visual perception mechanism in human primary visual pathway. Firstly, the spatio-temporal coding of neural information is realized on the basis of the Gaussian derivative function, and then the texture and background are suppressed by the non-classical receptive field. In addition, we propose a neural coding that can strengthen the redundancy of visual information in the optic radiation area to enhance the contour information and robustness of detecting. Finally, primary contour is fed forward to the primary visual cortex to achieve rapid adjustment of the contour response. In this paper, the RuG40 library is taken for processing, acquiring the contour detecting result through the non-maximal suppression and hysteresis threshold, and mean values $P$ of optimal parameters for whole dataset and each image are 0.48 and 0.55, respectively, compared with the ground truth. In addition, the FPS of algorithm reaches 1/2. The results indicate the new method in this paper can effectively highlight the principal contour and suppress texture region which will provide a new idea for subsequent image comprehension and analysis.