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Applied Sciences
Volume 16
Issue 12
10.3390/app16126061
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Unified Texture Descriptor in the Form of Color and Machine Learning, Applied to Face Identification

by
Jorge Aguilar-Santiago
1,
Cuauhtémoc Acosta-Lúa
2,
Ariadna-Berenice Flores-Jiménez
1,
Carlos-Eduardo Padilla-Leyferman
1,
Juan-Carlos Estrada-Gutiérrez
2,
María-Eugenia Sánchez-Morales
2 and
Maricela Jiménez-Rodríguez
1,*
1
Department of Basic Sciences, La Ciénega University Center, University of Guadalajara, Av. Universidad No. 1115, Lindavista, Ocotlán 47810, Jalisco, Mexico
2
Department of Technological Sciences, La Ciénega University Center, University of Guadalajara, Av. Universidad No. 1115, Lindavista, Ocotlán 47810, Jalisco, Mexico
*
Author to whom correspondence should be addressed.
Appl. Sci. 2026, 16(12), 6061; https://doi.org/10.3390/app16126061 (registering DOI)
Submission received: 20 May 2026 / Revised: 8 June 2026 / Accepted: 11 June 2026 / Published: 15 June 2026
(This article belongs to the Special Issue Image Processing: Technologies, Methods, Apparatus)
Versions Notes

Abstract

Facial recognition is widely employed in identification systems where access restriction is a desirable quality, providing greater security and preventing the access of unauthorized parties. With this problem in mind, this paper proposes a new texture descriptor that works in the RGB, YCbCr and HSV color modes. It obtains perceptual descriptive data from the photographs; the descriptor considers similarities between neighboring pixels and diminishing noise interference, making it robust to minor disturbances and bringing greater stability between similar images. Furthermore, the descriptor achieves good classification performance when used with both a neural network (NN) and the statistical classifier Support Vector Machine (SVM) on color images. A performance comparison of the proposed descriptor against LBP and OC_LBP employing three different face databases is presented to demonstrate that the proposed descriptor can work with the RGB, YCbCr and HSV color modes, presenting the best results when employing a neural network as a classifier with color image databases in the three studied color modes.
Keywords: texture descriptors; SVM; neural networks; YCbCr; RGB; HSV; facial recognition texture descriptors; SVM; neural networks; YCbCr; RGB; HSV; facial recognition

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MDPI and ACS Style

Aguilar-Santiago, J.; Acosta-Lúa, C.; Flores-Jiménez, A.-B.; Padilla-Leyferman, C.-E.; Estrada-Gutiérrez, J.-C.; Sánchez-Morales, M.-E.; Jiménez-Rodríguez, M. Unified Texture Descriptor in the Form of Color and Machine Learning, Applied to Face Identification. Appl. Sci. 2026, 16, 6061. https://doi.org/10.3390/app16126061

AMA Style

Aguilar-Santiago J, Acosta-Lúa C, Flores-Jiménez A-B, Padilla-Leyferman C-E, Estrada-Gutiérrez J-C, Sánchez-Morales M-E, Jiménez-Rodríguez M. Unified Texture Descriptor in the Form of Color and Machine Learning, Applied to Face Identification. Applied Sciences. 2026; 16(12):6061. https://doi.org/10.3390/app16126061

Chicago/Turabian Style

Aguilar-Santiago, Jorge, Cuauhtémoc Acosta-Lúa, Ariadna-Berenice Flores-Jiménez, Carlos-Eduardo Padilla-Leyferman, Juan-Carlos Estrada-Gutiérrez, María-Eugenia Sánchez-Morales, and Maricela Jiménez-Rodríguez. 2026. "Unified Texture Descriptor in the Form of Color and Machine Learning, Applied to Face Identification" Applied Sciences 16, no. 12: 6061. https://doi.org/10.3390/app16126061

APA Style

Aguilar-Santiago, J., Acosta-Lúa, C., Flores-Jiménez, A.-B., Padilla-Leyferman, C.-E., Estrada-Gutiérrez, J.-C., Sánchez-Morales, M.-E., & Jiménez-Rodríguez, M. (2026). Unified Texture Descriptor in the Form of Color and Machine Learning, Applied to Face Identification. Applied Sciences, 16(12), 6061. https://doi.org/10.3390/app16126061

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