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

  1. Canny, J., "A Computational Approach to Edge Detector", IEEE Transactions on PAMI, pp679- 698, 1986.
  2. Bovik, A. C., Huaung, T. S. and JR. D. C. M. "Nonparametric tests for edge detection noise", Pattern Recognition, 19:209-219, 1986.
  3. Yakimovsky Y., "Boundary and object detection in real world image", Journal ACM, 23:599-618, 1976.
  4. Raman Maini and J. S. Sobel, "Performance Evaluation of Prewitt Edge Detector for Noisy Images", GVIP Journal, Vol. 6, Issue 3, December 2006.
  5. Davis, L. S., "Edge detection techniques", Computer Graphics Image Process. (4), 248-270, 1995.
  6. Sharifi, M.; Fathy, M.; Mahmoudi, M.T.; "A classified and comparative study of edge detection algorithms", International Conference on Information Technology: Coding and Computing, Proceedings, Page(s):117 – 120, 8-10 April 2002.
  7. Shin, M.C.; Goldgof, D.B.; Bowyer, K.W.; Nikiforou, S.; " Comparison of edge detection algorithms using a structure from motion task", Systems, Man and Cybernetics, Part B, IEEE Transactions on Volume 31, Issue 4, Page(s):589-601, Aug. 2001.
  8. Heath M. , Sarker S., Sanocki T. and Bowyer K.,"Comparison of Edge Detectors: A Methodology and Initial Study", Proceedings of CVPR'96 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp.143-148, 1996.
  9. Rital, S.; Bretto, A.; Cherifi, H.; Aboutajdine, D.; "A combinatorial edge detection algorithm on noisy images", Video/Image Processing and Multimedia Communications 4th EURASIPIEEE Region 8 International Symposium on VIPromCom, Page(s):351 – 355, 16-19 June 2002.
  10. Li Dong Zhang; Du Yan Bi; "An improved morphological gradient edge detection algorithm", Communications and Information Technology, ISCIT 2005. IEEE International Symposium on Volume 2, Page(s):1280 – 1283, 12-14 Oct. 2005.
  11. Zhao Yu-qian; Gui Wei-hua; Chen Zhen-cheng; Tang Jing-tian; Li Ling-yun; "Medical Images Edge Detection Based on Mathematical Morphology" Engineering in Medicine and Biology Society, IEEEEMBS. 27th Annual International Conference, Page(s):6492 – 6495, 01-04 Sept. 2005.
  12. Fesharaki, M.N.; Hellestrand, G.R.; "A new edge detection algorithm based on a statistical approach", Speech, Image Processing and Neural Networks, Proceedings, ISSIPNN '94., International Symposium, Page(s):21 - 24 vol.1, 13-16 April 1994.

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.
Journal URL :

Article Preview