Comparision of Iris Identification by Using modified SIFT and SURF keypoint Descriptor

Nayak, Ritesh Kumar and Agarwal , Sharad (2013) Comparision of Iris Identification by Using modified SIFT and SURF keypoint Descriptor. BTech thesis.



A wide variety of systems require reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that only a legitimate user, access the rendered service. A biometrics system is essentially a pattern recognition system, which makes a personal identification by determining the authenticity of a specific physiological or behavioral characteristic possessed by the user. Iris serves as one of the excellent biometric traits due to the stability and randomness of its unique features. After localization of the iris, Scale Invariant Feature Transform (SIFT) is used to extract the local features. But SIFT is found out to be computational complex.So in this paper another keypoint descriptor ,Speeded Up Robust Features (SURF), is tested and then modified which compare the performance of different descriptor and hence gives promising results with very less computations. We finally carry out a comparision of both the descriptors performance wise.

Item Type:Thesis (BTech)
Uncontrolled Keywords:Biometrics, Feature Extraction, Iris Detection, SIFT, SURF
Subjects:Engineering and Technology > Electronics and Communication Engineering > Image Processing
Divisions: Engineering and Technology > Department of Electronics and Communication Engineering
ID Code:4764
Deposited By:Hemanta Biswal
Deposited On:31 Oct 2013 11:39
Last Modified:20 Dec 2013 11:52
Supervisor(s):Pati, U C

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