Multi-Threshold Algorithm Based on Havrda and Charvat Entropy for Edge Detection in Satellite Grayscale Images  

作　　者：Mohamed A. El-Sayed Hamida A. M. Sennari 

机构地区：[1]Department of Mathematics, Faculty of Science, Aswan University, Aswan, Egypt [2]Department of Mathematics, Faculty of Science, Fayoum University, Al Fayoum, Egypt

出　　处：《Journal of Software Engineering and Applications》2014年第1期42-52,共11页软件工程与应用（英文）

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.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 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]