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This work is licensed under a Creative Commons Attribution 4.0 International License.
Edge Detection in Images Based on Approximation Theory
HASSAN BADRY MOHAMED A. EL-OWNY Department of Mathematics, Faculty of Science, Aswan University, 81528 Aswan, Egypt Computer Science Department, Taif University, 21974 Taif, KSA
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Abstract: Edges characterize boundaries and edge detection is one of the most difficult tasks in image processing hence it is a problem of fundamental importance in image processing. Several edge detection algorithms have been developed such as Prewitt, Sobel, LOG, etc. But, they are not able to produce ideal or optimized results. This paper presents an edge detection approach applicable to gray level images based on Approximation Theory. The performance of proposed method is compared against other methods such as Sobel and Prewitt edge detector by using various tested images. Experimental results reveal that the proposed method exhibits better performance and may efficiently be used for the detection of edges in image.
Keywords: Edge detection, Approximation Theory, Gray scale images.
Keywords: Edge detection, Approximation Theory, Gray scale images.
How to Cite:
[1] HASSAN BADRY MOHAMED A. EL-OWNY Department of Mathematics, Faculty of Science, Aswan University, 81528 Aswan, Egypt Computer Science Department, Taif University, 21974 Taif, KSA, “Edge Detection in Images Based on Approximation Theory,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE)
This work is licensed under a Creative Commons Attribution 4.0 International License.