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JRTIP
2008

Automatic gender recognition based on pixel-pattern-based texture feature

10 years 2 months ago
Automatic gender recognition based on pixel-pattern-based texture feature
A pixel-pattern-based texture feature (PPBTF) is proposed for real-time gender recognition. A gray-scale image is transformed into a pattern map where edges and lines are to be used for characterizing the texture information. On the basis of the pattern map, a feature vector is comprised the numbers of the pixels belonging to each pattern. We use the image basis functions obtained by principal component analysis (PCA) as the templates for pattern matching. The characteristics of the feature are comprehensively analyzed through an application to gender recognition. Adaboost is used to select the most discriminative feature subset, and support vector machine (SVMs) is adopted for classification. Performed on frontal images from FERET database, the comparisons with Gabor show that PPBTF is a significant facial representation, quite effective and speedier in computation. Keywords Gender recognition
Huchuan Lu, Yingjie Huang, Yen-Wei Chen, Deli Yang
Added 27 Jan 2011
Updated 27 Jan 2011
Type Journal
Year 2008
Where JRTIP
Authors Huchuan Lu, Yingjie Huang, Yen-Wei Chen, Deli Yang
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