Please use this identifier to cite or link to this item:
|Title:||Face recognition using a DCT-HMM approach|
|Keywords:||Discrete Cosine Transforms|
Hidden Markov Models
|Citation:||Proceedings of the Fourth IEEE Workshop on Applications of Computer Vision, Princeton, USA, 19-21 October 1998, 226-231|
|Abstract:||A transform domain approach coupled with Hidden Markov Model (HMM) for face recognition is presented. JPEG kind of strategy is employed to transform input subimage for training HMMs. DCT transformed vectors efface images are used to train ergodic HMM and later for recognition. ORL face database of 40 subjects with 10 images per subject is used to evaluate the performance of the proposed method. 5 images per subject are used for training and the rest 5 for recognition. This method has an accuracy of 99.5%. The results, to the best of knowledge of the authors, give the best recognition percentage as compared to any other method reported so far on ORL face database.|
|Appears in Collections:||Proceedings papers|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.