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A New Fractional-Order Mask for Image Edge Detection Based on Caputo–Fabrizio Fractional-Order Derivative Without Singular Kernel

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Abstract

In this work, we consider the Caputo–Fabrizio fractional-order derivative to generalize the first-order Sobel operator. The resulting fractional mask is used to carry out edge analysis of medical images. The implementation of this method will allow enhancing the study, and the monitoring of diseases such as breast cancer, benign cyst, and breast calcifications, among others, to properly treat these diseases. The experimental results showed that the proposed operator gives superior performance over conventional integer-order operators because it can detect more edge details feature of the medical images, as well as it is more robust to noise.

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Acknowledgements

The authors are grateful to all of the anonymous reviewers for their valuable suggestions. Jorge Enrique Lavín Delgado and Jesús Emmanuel Solís Pérez acknowledge the support provided by CONACyT through the assignment post-doctoral and doctoral fellowship, respectively. José Francisco Gómez Aguilar acknowledges the support provided by CONACyT: Cátedras CONACyT para jóvenes investigadores 2014. José Francisco Gómez Aguilar and Ricardo Fabricio Escobar Jiménez acknowledge the support provided by SNI-CONACyT.

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Authors and Affiliations

  1. Tecnológico Nacional de México/CENIDET, Interior Internado Palmira S/N, Col. Palmira, C.P. 62490, Cuernavaca, Morelos, Mexico

    J. E. Lavín-Delgado, J. E. Solís-Pérez & R. F. Escobar-Jiménez

  2. CONACyT-Tecnológico Nacional de México/CENIDET, Interior Internado Palmira S/N, Col. Palmira, C.P. 62490, Cuernavaca, Morelos, Mexico

    J. F. Gómez-Aguilar

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  1. J. E. Lavín-Delgado
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All authors contributed equally and significantly in writing this article. All authors read and approved the final manuscript.

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Lavín-Delgado, J.E., Solís-Pérez, J.E., Gómez-Aguilar, J.F. et al. A New Fractional-Order Mask for Image Edge Detection Based on Caputo–Fabrizio Fractional-Order Derivative Without Singular Kernel. Circuits Syst Signal Process 39, 1419–1448 (2020). https://doi.org/10.1007/s00034-019-01200-3

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