Next Level of Data Fusion for Human Face Recognition

Details Next Level of Data Fusion for Human Face Recognition Next Level of Data Fusion for Human Face Recognition

2011-06-17

arxiv.org/abs/1106.3466v1

Proceedings of International Conference on Mathematical Modeling and Applications to Industrial Problems (MMIP' 11), National

Computer Science

Computer Vision and Pattern Recognition

Keywords: Thermal Image, Visual Image, Fused Image, Data Fusion, Wavelet decomposition, Decision Fusion, Classification

Scientific paper

This paper demonstrates two different fusion techniques at two different levels of a human face recognition process. The first one is called data fusion at lower level and the second one is the decision fusion towards the end of the recognition process. At first a data fusion is applied on visual and corresponding thermal images to generate fused image. Data fusion is implemented in the wavelet domain after decomposing the images through Daubechies wavelet coefficients (db2). During the data fusion maximum of approximate and other three details coefficients are merged together. After that Principle Component Analysis (PCA) is applied over the fused coefficients and finally two different artificial neural networks namely Multilayer Perceptron(MLP) and Radial Basis Function(RBF) networks have been used separately to classify the images. After that, for decision fusion based decisions from both the classifiers are combined together using Bayesian formulation. For experiments, IRIS thermal/visible Face Database has been used. Experimental results show that the performance of multiple classifier system along with decision fusion works well over the single classifier system.

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