Abstract：To detect the edge of noisy image, an adaptive thresholding based edge detection approach is proposed. In this approach, the differential operators of the two-dimensional Gaussian function are used to design the multi-oriented edge detection filter. The image gradient is computed based on the designed filters. To reduce the effect of noise to the gradient image, an adaptive method is proposed to determine the filter size based on the candidate thresholds. After the filter size is determined, an adaptive thresholding method is proposed to select the hysteresis threshold. The proposed edge detection approach is evaluated under different noise conditions in experiments. The relationships among filter sizes, hysteresis thresholds and the proposed algorithm performance are studied. Experimental results demonstrate that the proposed approach determines the filter size and hysteresis threshold based on the image noise adaptively and it produces good anti-noise performance.
作者简介: 李敏花(通讯作者)，女，1981年生，博士，副教授，主要研究方向为图像处理、模式识别、机器视觉.E-mail:minhuali09@163.com. (LI Minhua(Corresponding author)， born in 1981， Ph. D.， associate professor. Her research interests include image processing， pattern recognition and computer vision.)
引用本文:
李敏花，柏猛，吕英俊. 自适应阈值图像边缘检测方法*[J]. 模式识别与人工智能, 2016, 29(2): 177-184.
LI Minhua, BAI Meng, Lü Yingjun. Adaptive Thresholding Based Edge Detection Approach for Images. , 2016, 29(2): 177-184.
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