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Feature extraction using gabor-filter and recursive fisher linear discriminant with application in fingerprint identification

Dadgostar, M ; Sharif University of Technology | 2009

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  1. Type of Document: Article
  2. DOI: 10.1109/ICAPR.2009.64
  3. Publisher: 2009
  4. Abstract:
  5. Fingerprint is widely used in identification and verification systems. In this paper, we present a novel feature extraction method based on Gabor filter and Recursive Fisher Linear Discriminate (RFLD) algorithm, which is used for fingerprint identification. Our proposed method is assessed on images from the biolab database. Experimental results show that applying RFLD to a Gabor filter in four orientations, in comparison with Gabor filter and PCA transform, increases the identification accuracy from 85.2% to 95.2% by nearest cluster center point classifier with Leave-One-Out method. Also, it has shown that applying RFLD to a Gabor filter in four orientations, in comparison with Gabor filter and PCA transform, increases the identification accuracy from 81.9% to 100% by 3NN classifier. The proposed method has lower computational complexity and higher accuracy rates than conventional methods based on texture features © 2009 IEEE
  6. Keywords:
  7. Accuracy rates ; Cluster centers ; Conventional methods ; Feature extraction methods ; Fingerprint identifications ; Fisher linear discriminants ; Gabor filters ; Identification accuracies ; Leave-one-out methods ; Texture features ; Verification systems ; Classifiers ; Computational complexity ; Learning systems ; Mathematical transformations ; Recursive functions ; Feature extraction
  8. Source: Proceedings of the 7th International Conference on Advances in Pattern Recognition, ICAPR 2009, 4 February 2009 through 6 February 2009, Kolkata ; 2009 , Pages 217-220 ; 9780769535203 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/4782778