Neuro Fuzzy Q-Learning Optimized Approach for Solving Latent Fingerprint Recognition |
Author(s): |
| Yogiraj Bhale , DIMAT,Raipur; Somesh Dewangan, DIMAT,Raipur |
Keywords: |
| Neuro Fuzzy, Q-Learning |
Abstract |
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Fingerprint recognition is one of the most important techniques used in the field of biometric identification. This paper presents a latent fingerprint recognition technique followed by Q-learning approach for forensic application. Due to small area of the fingers and low quality it is necessary to extract all the features of the fingerprint for the effective matching. For minutia extraction Q-learning algorithm is used. The proposed method uses fuzzy & neural network for high recognition rate, high accuracy and it takes less time for recovery. The steps for this method are Fingerprint Acquisition, Fingerprint Enhancement using decomposition method and by median filter, Minutia Extraction using Q-learning algorithm, Removal of false Minutia using distance computation method & fingerprint recognition using neuro- fuzzy rule and neural network. |
Other Details |
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Paper ID: IJSRDV3I40965 Published in: Volume : 3, Issue : 4 Publication Date: 01/07/2015 Page(s): 3026-3031 |
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