Gender Recognition Using Local Binary Pattern and Naive Bayes Classifier
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Date
2016
Journal Title
Journal ISSN
Volume Title
Publisher
Nigeria Computer Society (NCS), Lagos, Nigeria - The Journal of Computer Science and Its Application, An International Journal of the Nigeria Computer Society. 23(1), 65 – 74
Abstract
Human face provides important visual information for gender perception. Ability to
recognize a particular gender is very important for the purpose of differentiation. Automatic
gender classification has many important applications, for example, intelligent user interface,
surveillance, identity authentication, access control and human-computer interaction amongst
others. Gender recognition is a fundamental task for human beings, as many social functions
critically depend on the correct gender perception. Consequently, real-world applications
require gender classification on real-life faces, which is much more challenging due to
significant appearance variations in unconstrained scenarios. In this study, Local Binary
Pattern is used to detect the occurrence of a face in a given image by reading the texture change
within the regions of the image, while Naive Bayes Classifier was used for the gender
classification. From the results obtained, the gender correlation was 100% and the highest
accuracy of the result obtained was 99%.The system can be employed for use in scenarios
where real time gender recognition is required.
Keywords: Gender, Local Binary Pattern, Naïve Bayes, Recognition