文件名称:ijabr201605104_Aryan
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Edge detection is widely used in image processing, image recognition and computer vision. Tradition edge detection
methods have a lot of disadvantages. This paper presents a new edge detection algorithm base on Matching Pursuit
(MP). Our method has four steps. Firstly, the color image is converted to gray Image. Secondly, the residual part of
Matching Pursuit algorithm with the Wavelet Packet dictionary is extracted. Thirdly, the Gaussian Filter is applied to
remove the additional parts of the previous image and finally, the Ostu’s thresholding method converts image to
binary form. We compared our algorithm with the tradition methods like Prewitt, Sobel, Laplacian of Gaussian (LOG)
and Canny operators. Results show that our algorithm has high value of Performance parameters such as PR, PSNR
and FOM compared to other algorithms.
methods have a lot of disadvantages. This paper presents a new edge detection algorithm base on Matching Pursuit
(MP). Our method has four steps. Firstly, the color image is converted to gray Image. Secondly, the residual part of
Matching Pursuit algorithm with the Wavelet Packet dictionary is extracted. Thirdly, the Gaussian Filter is applied to
remove the additional parts of the previous image and finally, the Ostu’s thresholding method converts image to
binary form. We compared our algorithm with the tradition methods like Prewitt, Sobel, Laplacian of Gaussian (LOG)
and Canny operators. Results show that our algorithm has high value of Performance parameters such as PR, PSNR
and FOM compared to other algorithms.
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ijabr201605104_Aryan.pdf