Comparison of Various Image Edge Detection Techniques for Brain Tumor Detection

Authors(2) :-Jennifer P., Dr. D. Devi Aruna

Brain tumors are created by abnormal and uncontrolled cell division in brain itself. If the growth becomes more than 50%, then the patient is not able to recover. So the detection of brain tumor needs to be fast and accurate. In this paper the comparative analysis of various Image Edge Detection techniques is presented. The experiment is conducted using MATLAB 7.0. It has been shown that the Cannyís edge detection algorithm performs better than all these operators under almost all scenarios. Evaluation of the images showed that under noisy conditions Canny, LoG( Laplacian of Gaussian), Robert, Prewitt, Sobel exhibit better performance, respectively. It has been observed that Cannyís edge detection algorithm is computationally more expensive compared to LoG( Laplacian of Gaussian), Sobel, Prewitt and Robertís operator.

Authors and Affiliations

Jennifer P.
Department of Computer Applications Dr.N.G.P Arts and Science College Coimbatore, Tamil Nadu, India
Dr. D. Devi Aruna
Department of Computer Applications Dr.N.G.P Arts and Science College Coimbatore, Tamil Nadu, India

Brain Tumor, Edge Detection, Canny, Laplacian of Gaussian, Robert, Prewitt, Sobel

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Publication Details

Published in : Volume 2 | Issue 1 | January-February 2017
Date of Publication : 2017-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 231-235
Manuscript Number : CSEIT172153
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Jennifer P., Dr. D. Devi Aruna, "Comparison of Various Image Edge Detection Techniques for Brain Tumor Detection", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 1, pp.231-235, January-February.2017
URL : http://ijsrcseit.com/CSEIT172153

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