Analytical Approach For Privacy Protection By Palm Print Mechanism Using Wavelet Transformation (International Journal of Engineering and Computer Science, 2015)
The prominence of digital image processing domain has been increased from last few decades due to its advanced research areas such as medicine, biometrics, military, robotics etc. In this work an important issue has taken as area of research namely protecting the privacy information from the unauthenticated users either as accidental or incidental ways. Although tremendous progress has been made in the past years on the protecting the privacy information by make use of biometrics namely fingerprint, palm print, iris etc. The usage of palm print in academia, medical labs, and military has been increased from few years but in some scenarios these palm print mechanisms fails to meet the practical requirement. The proposed work presents a novel work where palm print approach uses textural information along with the different wavelet transforms in order to protect the privacy information where the information from different transform techniques is analyzed in terms of individual as well as combined level. Biorthogonal, Symlet and Discrete Meyer are the wavelet transform techniques used in the proposed work for the analysis on the palm images taken from the image acquisition system. Finally when compare with the traditional palm print approaches the proposed palm print algorithms has better genuine acceptance rate i.e. GAR is 97.12%.