An Improved Canny Edge Detection Algorithm Based on Type-2 Fuzzy Sets

被引：71

作者：

Biswas, Ranita ^{[1
]}

Sil, Jaya ^{[1
]}

机构：

[1] Bengal Engn & Sci Univ, Dept Comp Sci & Technol, Sibpur 711103, Howrah, India

来源：

2ND INTERNATIONAL CONFERENCE ON COMPUTER, COMMUNICATION, CONTROL AND INFORMATION TECHNOLOGY (C3IT-2012) | 2012年 / 4卷

关键词：

Canny edge detection; Type-2 fyzzy sets; Automatic threshold selection;

D O I：

10.1016/j.protcy.2012.05.134

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Canny's edge detection algorithm is a classical and robust method for edge detection in gray-scale images. The two significant features of this method are introduction of NMS (Non-Maximum Suppression) and double thresholding of the gradient image. Due to poor illumination, the region boundaries in an image may become vague, creating uncertainties in the gradient image. In this paper, we have proposed an algorithm based on the concept of type-2 fuzzy sets to handle uncertainties that automatically selects the threshold values needed to segment the gradient image using classical Canny's edge detection algorithm. The results show that our algorithm works significantly well on different benchmark images as well as medical images (hand radiography images). (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of C3IT

引用

页码：820 / 824

页数：5

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