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Weber local descriptor for image analysis and recognition: a survey

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Abstract

Weber local descriptor (WLD) is applied for addressing the challenges in image/pattern problems, especially in computer vision and pattern recognition domains. In this paper, we review literature on theories and applications of WLD. Using WLD, we address the different challenges of image analysis and recognition features with respect to illumination changes, contrast differences, and geometrical transformations like rotation, scaling, translation, and mirroring. Further, the role of the classifiers and experimental protocols used in the different applications are discussed. Applications include texture classification, medical imaging, agricultural safety, fingerprint analysis, forgery analysis, and face recognition.

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Acknowledgements

Authors are thankful to CMATER LAB, CSE Dept., Jadavpur university for getting the well and good infrastructure during this work. The first author is also grateful to Dr. B. C. Roy Polytechnic, Durgapur for the overall support during the progress of this work. The work is partially supported by the SERB, GOI via project no SB/S3/EECE/054/2016. Also, the authors would like to acknowledge Sk Md Obaidullah for his initial discussion.

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  1. Jadavpur University, Kolkata, West Bengal, 700032, India

    Arnab Banerjee & Nibaran Das

  2. University of South Dakota, Vermillion, SD, 57069, USA

    K. C. Santosh

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A.B., N.D. and K.C.S.: Conceptualization and Methodology. A.B. and N.D.: Writing- Original draft preparation. N.D. and K.C.S.: Supervision. K.C.S.: Writing- Reviewing and Editing

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Banerjee, A., Das, N. & Santosh, K.C. Weber local descriptor for image analysis and recognition: a survey. Vis Comput 38, 321–343 (2022). https://doi.org/10.1007/s00371-020-02017-x

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