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Article

Postprocessing for Skin Detection

1
Department of Information Engineering (DEI), University of Padova, 35131 Padova, Italy
2
Department of Information Technology and Cybersecurity, Missouri State University, Springfield, MO 65804, USA
3
Department of Computer Science and Engineering (DISI), University of Bologna, 47521 Cesena, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Jean-Yves Ramel
J. Imaging 2021, 7(6), 95; https://doi.org/10.3390/jimaging7060095
Received: 21 April 2021 / Revised: 24 May 2021 / Accepted: 28 May 2021 / Published: 3 June 2021
Skin detectors play a crucial role in many applications: face localization, person tracking, objectionable content screening, etc. Skin detection is a complicated process that involves not only the development of apposite classifiers but also many ancillary methods, including techniques for data preprocessing and postprocessing. In this paper, a new postprocessing method is described that learns to select whether an image needs the application of various morphological sequences or a homogeneity function. The type of postprocessing method selected is learned based on categorizing the image into one of eleven predetermined classes. The novel postprocessing method presented here is evaluated on ten datasets recommended for fair comparisons that represent many skin detection applications. The results show that the new approach enhances the performance of the base classifiers and previous works based only on learning the most appropriate morphological sequences. View Full-Text
Keywords: segmentation; skin detector; convolutional neural networks; postprocessing segmentation; skin detector; convolutional neural networks; postprocessing
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MDPI and ACS Style

Baldissera, D.; Nanni, L.; Brahnam, S.; Lumini, A. Postprocessing for Skin Detection. J. Imaging 2021, 7, 95. https://doi.org/10.3390/jimaging7060095

AMA Style

Baldissera D, Nanni L, Brahnam S, Lumini A. Postprocessing for Skin Detection. Journal of Imaging. 2021; 7(6):95. https://doi.org/10.3390/jimaging7060095

Chicago/Turabian Style

Baldissera, Diego, Loris Nanni, Sheryl Brahnam, and Alessandra Lumini. 2021. "Postprocessing for Skin Detection" Journal of Imaging 7, no. 6: 95. https://doi.org/10.3390/jimaging7060095

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