A Multi-Level Threshold Method for Edge Detection and Segmentation Based on Entropy
作者机构：Department of MathematicsFaculty of ScienceFayoum UniversityFayoumEgypt.CurrentlyComputer Science DepartmentTaif UniversityTaifSaudi Arabia Computer Science DepartmentFaculty of Computers and Information Minia UniversityMiniaEgypt Department of MathematicsFaculty of ScienceAswan UniversityAswanEgypt
出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)
年 卷 期：2020年第63卷第4期
页 面：1-16页
核心收录：
学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）]
主 题：Multi-level threshold edge detection 2D histogram entropy
摘 要：The essential tool in image processing,computer vision and machine vision is edge detection,especially in the fields of feature extraction and feature *** is a basic area in information *** entropy,in image processing field has a role associated with image *** an initial step in image processing,the entropy is always used the image’s segmentation to determine the regions of image which is used to separate the background and objects in *** segmentation known as the process which divides the image into multiple regions or sets of *** applications have been development to enhance the image *** paper utilizes the Shannon entropy to achieve edge detection process and segmentation of the *** introduces a new method of edge detection for 2-D histogram and Shannon entropy based on multilevel *** method utilizes the gray value and the average gray value of the pixels to achieve the two dimensional *** current method has apriority in comparison to some upper classical *** experimental results exhibited that the proposed method could capture a moderate quality and execution time better than other comparative methods,particularly in the largest images *** proposed method offers good results when applied with images of different sizes from the civilization of ancient Egyptians.
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