A Minimum and Maximum of Regional Information Method to Improve the Sobel Edge Detector

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Advances in Information, Communication and Cybersecurity (ICI2C 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 357))

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Abstract

Edge detection is the most common approach for detecting meaningful discontinuities in grayscale images. In this paper we develop an improved edge detector based on Sobel method which produces promising results. We analyze the effect of considering the minimum and maximum of the regional information around a given pixel in the stage of the gradient computation. We treat each image as a set of dark or bright regions depending on a predetermined threshold. Then, we create a pixel set by linearly increasing or decreasing the range of the image intensities. To finish, the edge map and direction map are generated. We experimentally demonstrate that the method is competitive with some conventional methods such as Sobel, Prewitt and Canny.

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Acknowledgment

The authors are very thankful to anonymous Editors and Reviewers for their careful reading and valuable comments and suggestions.

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Bouda, B., Alifdal, A. (2022). A Minimum and Maximum of Regional Information Method to Improve the Sobel Edge Detector. In: Maleh, Y., Alazab, M., Gherabi, N., Tawalbeh, L., Abd El-Latif, A.A. (eds) Advances in Information, Communication and Cybersecurity. ICI2C 2021. Lecture Notes in Networks and Systems, vol 357. Springer, Cham. https://doi.org/10.1007/978-3-030-91738-8_2

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