Evaluating the Performance of Some Edge Detection Algorithms
Abstract
Despite the widespread use of image processing systems in various areas of life, but the great challenge facing these systems is to provide sufficient storage size images as the large volume of data inherent to image processing applications. So it was the development of many image processing techniques in order to solve this problem and the most important techniques is the edge detection.
Edge detection has applications in all areas of research, including medical imaging, locate objects in satellite images (roads, forests, etc.), face recognition, fingerprint recognition, traffic control systems, brake light detection …, etc.
This research presents a comparative study between a set of edge detection algorithms Canny, Deriche, ShenCastan,,Kirsch,MarrHildreth,Sobel, Prewitt, LaplaceI, and LaplaceII, under the impact of several factors, including the impact of lighting, noise, and employment.
All of these algorithms are applied on several types of gray images.
The results were compared and discussed, the suitable algorithms is suggested to apply on various types of images, according to the impart of each factor.
Visual studio is used to design a user interface to apply various edge detection algorithms, which are programmed using C++.
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