An efficient and robust face detection method using neuro-fuzzy approach

Person identification plays a major role in any secured and safety system. Face is one of the major biometric explored by many researchers for human identification. The problem becomes more complex by means of any occlusion of objects, due to different illumination, expression and pose. We propose a...

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Bibliographic Details
Main Authors: Logesh, S., Bharathi, S. A., Chandra Mouli, P. V. S. S. R.
Format: Conference Proceeding
Language:English
Subjects:
Biological neural networks
Face
Face detection
Feature extraction
Fusion
Fuzzy Sets
Information processing
Neural Networks
Neurons
Training
Online Access:Request full text
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Summary:Person identification plays a major role in any secured and safety system. Face is one of the major biometric explored by many researchers for human identification. The problem becomes more complex by means of any occlusion of objects, due to different illumination, expression and pose. We propose a novel pattern recognition approach for face detection in this paper. The approach presented is an amalgamation of artificial neural networks and fuzzy set theory. The proposed method runs in two phases and fuses the results for better performance and accuracy. The proposed method has been tested on BioID dataset and got 94% accuracy.
DOI:10.1109/ICIIP.2011.6108976