TITLE:
Multi-Threshold Algorithm Based on Havrda and Charvat Entropy for Edge Detection in Satellite Grayscale Images
AUTHORS:
Mohamed A. El-Sayed, Hamida A. M. Sennari
KEYWORDS:
Multi-Threshold; Edge Detection; Measure Entropy; Havrda & Charvat’s Entropy
JOURNAL NAME:
Journal of Software Engineering and Applications,
Vol.7 No.1,
January
17,
2014
ABSTRACT: 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.