Abstract
In this paper we generalize some classical edge detectors using the second-order Riesz fractional derivative. Taking advantages of fractional differential method we improve the shortcomings of conventional operators like Roberts, Prewitt and Sobel. Consequently, three improved edge detection algorithms are gained. The experimental results show that the proposed models enhance edge information effectively and reveal more detailed information than traditional operators.
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Georgescu, C. (2018). Improved Edge Detection Algorithms Based on a Riesz Fractional Derivative. In: Campilho, A., Karray, F., ter Haar Romeny, B. (eds) Image Analysis and Recognition. ICIAR 2018. Lecture Notes in Computer Science(), vol 10882. Springer, Cham. https://doi.org/10.1007/978-3-319-93000-8_23
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DOI: https://doi.org/10.1007/978-3-319-93000-8_23
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