Fingerprint matching using multi-dimensional ANN |
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| Authors: | Rajesh Kumar BR Deva Vikram |
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| Affiliation: | 1. Faculty of Engineering, Zagazig university, Zagazig, Egypt;2. Department of Computer Science and Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf 32952, Egypt;3. Department of Electrical Engineering, Menoufia University, 32511 Shebin El-kom, Egypt;4. Faculty of computers and information, Menofia University, Shebin Elkom, Egypt;5. Department of Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, Menouf 32952, Egypt;6. Department of Information Technology, College of Computers and Information Technology, Taif University, Al-Hawiya 21974, Kingdom of Saudi Arabia;1. School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou 221006, China;2. Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, V6T1Z4 Canada |
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| Abstract: | Fingerprint matching is one of the most widely used biometric technique for personal identification. This identification is achieved in this work by using the concept that every fingerprint has a unique pattern of distribution of the minutiae points. In this paper, a new method of recognition of this pattern of distribution of the minutiae points of an enhanced image is considered by using a multi-dimensional artificial neural network (MDANN). The proposed technique has the distinct advantage of using the entire resized minutiae image as an input at once. It is capable of excellent pattern recognition properties as the distribution of the minutiae points are used directly for recognition. The proposed approach shows significant promise and potential for improvement, compared with the other conventional matching techniques with regard to time and efficiency of results. |
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