In this paper we have proposed a gender recognition system through facial images. We have used three different techniques that involve Bandlet Trans-form (a multi-resolution technique), LBP (Local Binary Pattern) and mean to create the feature vectors of the images. To classify the images for gender, we have used fuzzy c mean clustering. SUMS and FERET databases were used for testing. Experimental results have shown that the maximum average accuracy was achieved using SUMS, 97.1% has been achieved using Band-lets and mean technique, Bandlets and whole image LBP has shown 85.13% and Bandlets with blocked based LBP has shown 87.02% average accuracy.
CITATION STYLE
Shabbir, Z., Khan, A. U., Irtaza, A., & Mahmood, M. T. (2015). A fuzzy logic approach for gender recognition from face images with embedded bandlets. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 9119, pp. 626–637). Springer Verlag. https://doi.org/10.1007/978-3-319-19324-3_56
Mendeley helps you to discover research relevant for your work.