期刊名称：Journal of Software Engineering and Applications
印刷版ISSN：1945-3116
电子版ISSN：1945-3124
出版年度：2014
卷号：7
期号：1
页码：42-52
DOI：10.4236/jsea.2014.71005
出版社：Scientific Research Publishing
摘要：Automatic edge detection of an image is considered a
type of crucial information that can be extracted by applying detectors with
different techniques. It is a main tool in pattern recognition, image
segmentation, and scene analysis. This paper introduces an edge-detection algorithm, which generates multi-threshold values. It is based on non-Shannon
measures such as Havrda &
Charvat’s entropy, which is commonly used in gray level image analysis in many
types of images such as satellite grayscale images. The proposed edge detection
performance is compared to the previous classic methods, such as Roberts,
Prewitt, and Sobel methods. Numerical results underline the robustness of the
presented approach and different applications are shown.
关键词：Multi-Threshold; Edge Detection; Measure Entropy; Havrda & Charvat’s Entropy
