An automated feature-localisation algorithm for a feature-specific modular approach for face recognition
by Praveen Sankaran, Rajkiran Gottumukkal, Vijayan K. Asari
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 2, No. 4, 2007

Abstract: Novel techniques for accurate location of the eyes and nose of a person in a complex-lighting environment are presented in this paper. An adaptive progressive thresholding technique is applied to spot the darkest regions representing the eyes in a face. The nose region is located by performing cumulative histogram-based thresholding of the gradient image formed below the eye region. A feature-specific modular Principal Component Analysis (PCA) approach on face images is performed with the identified features for face recognition. Principal components are extracted from non-overlapping modules of the image and are concatenated to make a single signature vector to represent the face in a particular viewing angle. Additional principal components are extracted from the key facial features and are added as an extension to the signature vector. The feature-specific modular PCA approach is capable of recognising faces in varying illumination conditions and facial expressions, as the modular components represent the local information of the facial regions.

Online publication date: Tue, 12-Jun-2007

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