边缘检测
人工智能
Canny边缘检测器
模式识别(心理学)
灰度
噪音(视频)
模糊逻辑
图像处理
计算机科学
GSM演进的增强数据速率
自适应神经模糊推理系统
计算机视觉
推论
微分边缘检测器
图像渐变
滤波器(信号处理)
数学
图像(数学)
模糊控制系统
作者
Wenwei Song,Xiaorong Gao,Jinlong Li,Lin Luo,Jianping Peng
摘要
Edge detection is a crucial task in image processing. Owing to the similarity in property between edges and noise, which demonstrates abrupt changes in image grayscale values, traditional edge detection methods are insufficient in detecting weak edges. Therefore, a local multi-threshold fuzzy inference method (LMFI) is introduced. Considering the binarization processing prior to conducting a fuzzy inference, to retain more edge information, a local threshold processing method and a triple threshold processing method are proposed. To reduce noise interference, an improved sigma filter and an improved fuzzy inference strategy are presented. The experimental results show that the effect of weak edge detection is improved by LMFI, when compared to conventional methods such as the original fuzzy inference algorithm and Canny edge detection algorithm.
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