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A Novel Face Segmentation Algorithm from a Video Sequence for Real-Time Face Recognition

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The first step in an automatic face recognition system is to localize the face region in a cluttered background and carefully segment the face from each frame of a video sequence. In this paper, we propose a fast and efficient algorithm for segmenting a face suitable for recognition from a video sequence. The cluttered background is first subtracted from each frame, in the foreground regions, a coarse face region is found using skin colour. Then using a dynamic template matching approach the face is efficiently segmented. The proposed algorithm is fast and suitable for real-time video sequence. The algorithm is invariant to large scale and pose variation. The segmented face is then handed over to a recognition algorithm based on principal component analysis and linear discriminant analysis. The online face detection, segmentation, and recognition algorithms take an average of 0.06 second on a 3.2 GHz P4 machine.


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Correspondence to R. Srikantaswamy.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Srikantaswamy, R., Sudhaker Samuel, R.D. A Novel Face Segmentation Algorithm from a Video Sequence for Real-Time Face Recognition. EURASIP J. Adv. Signal Process. 2007, 051648 (2007) doi:10.1155/2007/51648

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  • Face Recognition
  • Video Sequence
  • Linear Discriminant Analysis
  • Recognition Algorithm
  • Face Region