The aim of present research work on palmprint recognition using discrete wavelet packet transform (DWPT) algorithm for feature extraction & ANFIS (Adaptive Neuro-Fuzzy Inference System) for palmprint matching. Biometrics based fingerprint, face, iris recognition has been investigated over many year. Palmprint recognition is an emerging technology in recent years due to the transaction frauds, security breaches and personal identification etc. compare to fingerprint, palmprint contain rich features like, principle line, wrinkles, ridges, and minute points, and it provides high standard security. This paper developing multibiometrics using left and right palmprint images and gives higher accuracy then single biometrics system. Registered IITD palmprint database is collected from IIT Delhi, biometric research library. It consist 2600 images from both left and right hand. This experiment perform palmprint recognition for enhance security using IITD database. MATLAB have been used as the programming tool to implement and investigate the performance of the segmentation and feature extraction method using image processing toolbox.
| Published in | International Journal of Mineral Processing and Extractive Metallurgy (Volume 2, Issue 2) |
| DOI | 10.11648/j.ijmpem.20170202.11 |
| Page(s) | 13-20 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2017. Published by Science Publishing Group |
Biometrics, Multibiometrics, Left and Right Palmprint Image, Feature Extraction, Discrete Wavelet Packet Transform (DWPT)
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APA Style
Komal Kashyap, Ekta Tamrakar. (2017). Accurate Personal Identification Using Left and Right Palmprint Images Based on ANFIS Approach. International Journal of Mineral Processing and Extractive Metallurgy, 2(2), 13-20. https://doi.org/10.11648/j.ijmpem.20170202.11
ACS Style
Komal Kashyap; Ekta Tamrakar. Accurate Personal Identification Using Left and Right Palmprint Images Based on ANFIS Approach. Int. J. Miner. Process. Extr. Metall. 2017, 2(2), 13-20. doi: 10.11648/j.ijmpem.20170202.11
AMA Style
Komal Kashyap, Ekta Tamrakar. Accurate Personal Identification Using Left and Right Palmprint Images Based on ANFIS Approach. Int J Miner Process Extr Metall. 2017;2(2):13-20. doi: 10.11648/j.ijmpem.20170202.11
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Download@article{10.11648/j.ijmpem.20170202.11,
author = {Komal Kashyap and Ekta Tamrakar},
title = {Accurate Personal Identification Using Left and Right Palmprint Images Based on ANFIS Approach},
journal = {International Journal of Mineral Processing and Extractive Metallurgy},
volume = {2},
number = {2},
pages = {13-20},
doi = {10.11648/j.ijmpem.20170202.11},
url = {https://doi.org/10.11648/j.ijmpem.20170202.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmpem.20170202.11},
abstract = {The aim of present research work on palmprint recognition using discrete wavelet packet transform (DWPT) algorithm for feature extraction & ANFIS (Adaptive Neuro-Fuzzy Inference System) for palmprint matching. Biometrics based fingerprint, face, iris recognition has been investigated over many year. Palmprint recognition is an emerging technology in recent years due to the transaction frauds, security breaches and personal identification etc. compare to fingerprint, palmprint contain rich features like, principle line, wrinkles, ridges, and minute points, and it provides high standard security. This paper developing multibiometrics using left and right palmprint images and gives higher accuracy then single biometrics system. Registered IITD palmprint database is collected from IIT Delhi, biometric research library. It consist 2600 images from both left and right hand. This experiment perform palmprint recognition for enhance security using IITD database. MATLAB have been used as the programming tool to implement and investigate the performance of the segmentation and feature extraction method using image processing toolbox.},
year = {2017}
}
TY - JOUR T1 - Accurate Personal Identification Using Left and Right Palmprint Images Based on ANFIS Approach AU - Komal Kashyap AU - Ekta Tamrakar Y1 - 2017/07/25 PY - 2017 N1 - https://doi.org/10.11648/j.ijmpem.20170202.11 DO - 10.11648/j.ijmpem.20170202.11 T2 - International Journal of Mineral Processing and Extractive Metallurgy JF - International Journal of Mineral Processing and Extractive Metallurgy JO - International Journal of Mineral Processing and Extractive Metallurgy SP - 13 EP - 20 PB - Science Publishing Group SN - 2575-1859 UR - https://doi.org/10.11648/j.ijmpem.20170202.11 AB - The aim of present research work on palmprint recognition using discrete wavelet packet transform (DWPT) algorithm for feature extraction & ANFIS (Adaptive Neuro-Fuzzy Inference System) for palmprint matching. Biometrics based fingerprint, face, iris recognition has been investigated over many year. Palmprint recognition is an emerging technology in recent years due to the transaction frauds, security breaches and personal identification etc. compare to fingerprint, palmprint contain rich features like, principle line, wrinkles, ridges, and minute points, and it provides high standard security. This paper developing multibiometrics using left and right palmprint images and gives higher accuracy then single biometrics system. Registered IITD palmprint database is collected from IIT Delhi, biometric research library. It consist 2600 images from both left and right hand. This experiment perform palmprint recognition for enhance security using IITD database. MATLAB have been used as the programming tool to implement and investigate the performance of the segmentation and feature extraction method using image processing toolbox. VL - 2 IS - 2 ER -
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