Abstract: It is very significant for contour detection to be widely used in such fields as target recognition,image segmentation and pattern recognition,etc.According to the principle of visual biology,researchers put forward contour detection methods for gray image,which achieved good results.However,the color information can represent most of the image information,and the role of if cannot be ignored when detecting contour.The CO model proposed by Kaifu Yang can extract the target contour from the image,but the execution efficiency of the model still need to be improved.In this paper,a contour detection model CRFM (Color-opponent Receptive Field) was proposed.According to visual information processing mechanism,the model simulates the response from receptive field of the retinal ganglion cells and the one from the lateral geniculate nucleus cells respecitvely.In addition,CRFM uses the partial derivative difference between two Gaussian functions having different scales to simulate the response of the double opponent receptive field in the primary visual cortex and the visual characteristics.Because the filter,which simulates the double opponent receptive field,usually produces small value,the speed is improved for computing the convolution between the filter and the image information,and the execution cost is decreased.BSDS300 database was used in the experiments.Results show that the CRFM model can obtain better performance,and has higher execution efficiency than the CO model which is very practical in realisteic application.

Key words: Receptive field,Contour detection,Color opponent,Model