Robust Palm-Print Feature for Human Identification
S. Adebayo Daramola1, Olujimi Ajayi2, Tiwalade Odu3
1Dr. S. Adebayo Daramola, Department of Electrical and Information Engineering, Covenant University, College of Science and Technology, Ota, Nigeria.
2Olujimi Ajayi, Department of Electrical and Information Engineering, Covenant University, College of Science and Technology, Ota, Nigeria.
3Tiwalade Odu, Department of Electrical and Information Engineering, Covenant University, College of Science and Technology, Ota, Nigeria.
Manuscript received on March 23, 2014. | Revised Manuscript received on April 11, 2014. | Manuscript published on April 30, 2014. | PP: 152-155 | Volume-3, Issue-4, April 2014. | Retrieval Number: D2946043414/2013©BEIESP
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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: Palm-print is a unique biometric trait commonly uses to distinguish people. Identification of people with aid of machine is needed to solve insecurity challenges in our society. Human palm-print is a good raw material for machine based identification systems. These systems require strong predominate feature from palm-print for successful operation. In this work, a discriminate feature that can be used to differentiate people accurately is extracted from palm-print image. Edge detected palm-print image is sliced into smaller image blocks through centre points thereafter robust feature vector is generated from these smaller image blocks. The new feature was experimental using feature plot and it is shown clearly that this feature will deliver excellent classification result.
Keywords: Centre points, City block distance, Image blocks, Palm-print.