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Study and Comparison of Various Image Edge Detection Techniques
Raman Maini, Himanshu Aggarwal
Pages - 1 - 11     |    Revised - 20-02-2009     |    Published - 15-03-2009
Volume - 3   Issue - 1    |    Publication Date - February 2009  Table of Contents
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KEYWORDS
Edge Detection, Noise, Digital Image Processing
ABSTRACT
Edges characterize boundaries and are therefore a problem of fundamental importance in image processing. Image Edge detection significantly reduces the amount of data and filters out useless information, while preserving the important structural properties in an image. Since edge detection is in the forefront of image processing for object detection, it is crucial to have a good understanding of edge detection algorithms. In this paper the comparative analysis of various Image Edge Detection techniques is presented. The software is developed 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
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322 Sridevi, M., & Mala, C. (2012). A Survey on Monochrome Image Segmentation Methods. Procedia Technology, 6, 548-555.
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