Feature Extraction of Iris and Palmprint Biometric System using Dwt
K.Sripal Reddy1, A.Vijaya Lakshmi2
1K.Sripal Reddy*, ECE department, Vardhaman College of Engineering, Hyderabad, India.
2A. Vijaya Lakshmi, ,ECE department, Vardhaman College of Engineering, Hyderabad, India.
Manuscript received on November 12, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on 30 November, 2019. | PP: 8743-8746 | Volume-8 Issue-4, November 2019. | Retrieval Number: D9058118419/2019©BEIESP | DOI: 10.35940/ijrte.D9058.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Much work is done on Iris Recognition, since few years. Many cases discussed about performance in view of image capturing and recognition. Daugman work is the most important related to iris biometric in early research. It is fair to say, it is base model for iris biometric. Almost the available iris systems are based on this work. A palm print is image of the palm area of a hand. It is either an image taken online or offline. It is one of the most familiar and promising biometric model for personal identity verification. It is tough task to differentiate lines and wrinkles without explicit definition. depends on the thickness and position of some key points we can define principal lines. In our work, we are taken the principal line magnitude is less than or equal to 1. we cannot consider broken lines. If it is the case broken point is treat as last point.
Keywords: Iris, Bio Metric, Lines, Wrinkles, Broken Lines.
Scope of the Article: Biomedical Computing.