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Vol.3 , No. 5, Publication Date: Sep. 29, 2016, Page: 26-35
| [1] | Kanaa Thomas F. N., Higher Technical Teacher Training College, University of Bamenda, Bambili, Cameroon; Laboratory of Electronics, Electrotechnics, Automation and Telecommunications, University of Douala, Douala, Cameroon. |
| [2] | Ele Pierre, University Institute of Technology, Laboratory of Electronics, Electrotechnics, Automation and Telecommunications, University of Douala, Douala, Cameroon. |
| [3] | Tchiotsop Daniel, Fotso Victor University Institute of Technology, Laboratory of Automation and Applied Computer Science, University of Dschang, Bandjoun, Cameroon. |
| [4] | Tonye Emmanuel, National Advanced School of Engineering, Laboratory of Electronics and Signal Processing, University of Yaounde I, Yaounde, Cameroon. |
This paper is presenting a new and robust fingerprint identification/verification method liable to minimize any risk of human loss and to preserve peace and freedom when fighting against terrorism in a context of high public insecurity. For that matter, a database of 200 fingerprint images from a Boko Haram risk region of Cameroon has been put in place on which a noteworthy method from the literature and the author’s algorithm were tested. For this last algorithm, the enhanced image is computed by convolution of the Gabor filter attached to the ridge orientation and the ridge frequency, with the normalized fingerprint image from the minutiae rough segmentation by global thresholding on the variance. The minutiae are extracted gradually with the local Sauvola’s thresholding, the parallel thinning algorithm of the ridges and the false minutiae removal technique based on its branch. A minutia alignment and an elastic matching algorithm based on the optimization of the bounding box tolerance parameters are then combined to provide the matching score of the input fingerprint. With an accuracy of 99.27% at the equal error rate position, an improvement of 33.91% is observed as gap between the classical and the new approaches. The improved technique faithfully recognizes the fingerprints of the same individual and strongly rejects two different individuals’ fingerprints. An innovative development is therefore ready for detecting genuine and intruders in control systems to better solve the identification and verification problems in high public insecurity environments where a high performance is henceforth imposed as critical and strategic requirement in the whole world.
Keywords
Biometrics, Fingerprint, Segmentation, Minutiae Matching, Gabor Filtering, Sauvola’s Thresholding
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