A Study on Edge Detection Techniques for Natural Image Segmentation
Saiful Islam1, Majidul Ahmed2
1Saiful Islam, Assistant Professor, Department of Computer Science, Dhamdhama Anchalik College, Dhamdhama-781349, Nalbari(Assam), India.
2Dr. Majidul Ahamed, Assistant Professor and HoD, Department of Information Technology, Guwahati Commerce College, Guwahati, Assam, India.
Manuscript received on 07 February 2013 | Revised Manuscript received on 21 February 2013 | Manuscript Published on 28 February 2013 | PP: 80-83 | Volume-2 Issue-3, February 2013 | Retrieval Number: C0426022313/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Natural image segmentation is one of the fundamental problems in image processing. Statistics of ‘natural images’ provides useful priors for solving under-constrained problems in Computer Vision. Image segmentation is the process of partitioning/subdividing an image into multiple meaningful regions or sets of pixels with respect to a particular application. Image segmentation is a critical and essential component of image analysis system. In literature, there are many image segmentation techniques. One of the most important techniques is Edge detection techniques for natural image segmentation. Edge detection is a fundamental tool for image segmentation. Edge detection methods transform original images into edge images benefits from the changes of grey tones in the image. In literature, there are many Edge detection techniques for image segmentation. In this paper, we used four Edge detection techniques for natural image segmentation and they are Roberts Edge detection, Sobel Edge detection, Prewitt Edge detection, and LoG Edge detection.
Keywords: Edge Detection Techniques, Image Segmentation, MATLAB.
Scope of the Article: Image analysis and Processing