Please use this identifier to cite or link to this item: http://hdl.handle.net/10266/1050
Title: PALM Print Verification Using LabVIEW
Authors: Chaudhary, Vivek
Supervisor: Singla, Sunil Kumar
Arora, A.S.
Keywords: LabVIEW, Palmprint
Issue Date: 16-Nov-2009
Abstract: The development of accurate and reliable security systems is a matter of wide interest, and in this context biometrics has seen as a highly effective automatic mechanism for personal authentication. Authentication by biometric verification is becoming increasingly common in corporate and public security systems, consumer products and point of sale applications. Many research groups are working on the development of the different authentication systems such as the fingerprint, iris, hand, palm print etc. by using biometrics. The palm print is the first defining characteristics and natural method to be used for recognition. Moreover, ease acceptance and non invasive nature as compared to other biometric traits make it a preferable trait to be used for authentication. In this thesis, an automated approach to palm print recognition has been developed and discussed. Particular emphasis has been given to the alignment method, for which a new alignment algorithm has been proposed. The proposed algorithm uses the detection of fingertip, lower corner and vertex of the hand to find out the misalignment. Then a region of interest i.e. palmprint has been extracted from each image. A feature vector for each ROI has been computed and a correlation is then computed between the query and reference image. The structural similarity and dissimilarity between the different images determines the authenticity of the subject. The proposed system is reliable and user friendly as it is developed in LabVIEW 6i. The availability of datalog files in LabVIEW makes it one of the most promising candidate for its usage as a database. Datalog files can access and manipulate data and complex data structures quickly and easily. It makes writing and reading much faster. The system developed in LabVIEW detects the user in almost real time with a reasonable accuracy and repeatability. The self developed database has been used in the present work and the experiments conducted shows that the 20% FAR and 18% FRR has been achieved with the proposed method.
Description: M.E. (Electronic Instrumentation and Control Engineering)
URI: http://hdl.handle.net/10266/1050
Appears in Collections:Masters Theses@EIED

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