A contour detection method based on non-classical receptive field subfield
10.16289/j.cnki.1002-0837.2025.01011
- VernacularTitle:基于非经典感受野亚区的轮廓检测方法
- Author:
Jingyan ZHANG
1
;
Yingle FAN
;
Tao FANG
Author Information
1. 杭州电子科技大学自动化学院,杭州 310018
- Keywords:
contour detection;
non-classical receptive subfiled;
visual pathway;
surround inhibition
- From:Space Medicine & Medical Engineering
2025;36(1):65-68,74
- CountryChina
- Language:Chinese
-
Abstract:
Objective This paper proposes a novel contour detection method inspired by the surround inhibition mechanism of the primary visual cortex.Methods The method involves simulating the response characteristics of the classical receptive field in the primary visual cortex to external stimuli and constructing a multi-directional two-dimensional Gabor filter model for extracting primary contours.A non-classical receptive subfield surround suppression model is proposed based on the structural characteristics of the non-classical receptive subfield for texture suppression.Additionally,a two-dimensional Gaussian function is used to simulate information processing by ganglion cells,and information is transmitted across levels to improve the response rate.Finally,the characteristics of capturing global information by the human eye are simulated to correct the contours and obtain the final contour map.Results Qualitative and quantitative analysis compared with other existing contour detection algorithms;The average accuracy(AP)of any 200 images in the BSDS500 reached 0.703.Conclusion the results show that the proposed algorithm can more effectively highlight the contour of the subject and suppress the texture background.
