Author Country (or Countries)

Saudi Arabia


In this paper, We proposed a novel edge detection algorithm based on Cumulative Residual Entropy (CRE). It is an essential concept in information theory. However, in our knowledge, it has relatively little consideration in image processing. Image thresholding and edge detection techniques play a crucial role in several of the tasks needed for pattern recognition and computer vision. In this paper, we have studied, implemented,and applied the CRE measure for edge detection. Firstly, We have defined a thresholding criterion based on the CRE measure that is related to the image. Secondly, the optimal solution is used to find edge detection image. The efficiency of the proposed approach proved by using examples from a different type of images. We have compared the proposed technique with several classic edge techniques on the same data set. The performance of the proposed method based on peak signal to noise ratio (PSNR) has been presented.

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