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Comparison of Various Image Edge Detection Techniques for Brain Tumor Detection

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  • Jennifer P
  • D. Devi Aruna

Abstract

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 Canny’s 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 Canny’s edge detection algorithm is computationally more expensive compared to LoG( Laplacian of Gaussian), Sobel, Prewitt and Robert’s operator.

Suggested Citation

  • Jennifer P & D. Devi Aruna, 2017. "Comparison of Various Image Edge Detection Techniques for Brain Tumor Detection," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 2(1), pages 231-235, February.
    • Handle: RePEc:jbh:ijsrcs:v2:y2017:i1:id:hcseit172153
    Note: Article URL: https://ijsrcseit.com/CSEIT172153
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