Texture Feature Extraction For Biometric Authentication using Partitioned Complex Planes in Transform Domain

Feature vector generation is an important step in biometric authentication. Biometric traits such as fingerprint, finger-knuckle prints, palmprint, and iris are rich in texture. This texture is unique and the feature vector extraction algorithm should correctly represent the texture pattern. In this paper a texture feature extraction methodology is proposed for these biometric traits. This method is based on one step transform of the two dimensional images and then using the intermediate transformation data to generate complex planes for feature vector generation. This method is implemented using Walsh, DCT, Hartley, Kekre Transform & Kekre Wavelets. Results indicate the effectiveness of the feature vector for biometric authentication.

@article{Bharadi2012,
  title     = {Texture Feature Extraction For Biometric Authentication using Partitioned Complex Planes in Transform Domain},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {2},
  number    = {1},
  year      = {2012},
  publisher = {The Science and Information Organization},
  note      = {Special Issue on Selected Papers from International Conference & Workshop On Emerging Trends In Technology 2012},
  author    = {Vinayak Ashok Bharadi},
  doi       = {10.14569/SpecialIssue.2012.020105},
  url       = {https://doi.org/10.14569/SpecialIssue.2012.020105}
}