Open AccessIdentification of Virus in Microscopic Image Using Genetic Algorithm
Author(s) -
N. Senthilkumaran,
R. Preethi
Publication year - 2019
Publication title -
asian journal of computer science and technology
Language(s) - English
Resource type - Journals
eISSN - 2583-7907
pISSN - 2249-0701
DOI - 10.51983/ajcst-2019.8.s2.2031
Subject(s) - edge detection , deriche edge detector , prewitt operator , canny edge detector , blob detection , sobel operator , image gradient , artificial intelligence , computer science , enhanced data rates for gsm evolution , computer vision , pattern recognition (psychology) , image segmentation , image (mathematics) , image processing
In this paper describes a several techniques of effective edge detection by using image segmentation. The image segmentation provides various techniques to detect the edges on image. The paper mainly focused on edge detection using matlab parameters and solved the many problems. Edge detection techniques have a several type of techniques. We have taken microscopic image, which affects the human body by making diseases through viruses and bacteria’s. Now analyze only about the major techniques: a.) Roberts edge detection, b) sobel edge detection, c) prewitt edge detection, d) log (laplacian of gaussian) edge detection, e) genetic edge detection and f) canny edge detection. We have applied above five techniques which are used in edge detection and got a result on microscopic images. Hence, we scope this paper defines and compares the variety of techniques and demand assures the genetic algorithm provides a better performance on edge detection using microscopic image.