Open AccessEdge detection based on augmented lagrangian method for lowquality medical images
Author(s) -
Vo Thi Hong Tuyet
Publication year - 2020
Publication title -
ho chi minh city open university journal of science - engineering and technology
Language(s) - English
Resource type - Journals
eISSN - 2734-9608
pISSN - 2734-9330
DOI - 10.46223/hcmcoujs.tech.en.8.1.910.2018
Subject(s) - canny edge detector , edge detection , artificial intelligence , enhanced data rates for gsm evolution , computer vision , computer science , process (computing) , image (mathematics) , medical imaging , image processing , operating system
Medical images are useful for the treatment process. They contain a lot of information on displaying abnormalities in your body. The contour of medical images is a matter of interest. In there, edge detection is a process prepared for boundaries. Therefore, the edge detection of medical images is very important. Other previous methods must sacrifice time for the accurate results. It is because the medical images in the real world have many impurities. In this paper, I propose a method of detecting edges in medical images which have impurities by using augmented lagrangian method to improve the Canny algorithm. My algorithm improves the ability to detect edges faster. Compared with other recent methods, the proposed method is more efficient.