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Development of Mobile Face Verification Based on Locally Normalized Gabor Wavelets

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@article{IJASEIT1352,
   author = {Fadhlan Hafizhelmi Kamaru Zaman and Ahmad Asari Sulaiman and Ihsan Mohd Yassin and Nooritawati Md Tahir and Zairi Ismael Rizman},
   title = {Development of Mobile Face Verification Based on Locally Normalized Gabor Wavelets},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {7},
   number = {4},
   year = {2017},
   pages = {1198--1205},
   keywords = {face recognition; Gabor wavelets; local approach; single sample; verification system},
   abstract = {In this paper, we present a mobile face verification framework for automated attendance monitoring as a solution for more efficient, portable and cost-effective attendance monitoring systems. We use Raspberry Pi as mobile embedded input module connecting the webcam and radio frequency identification (RFID) reader to the personal computer (PC) which provides mobility due to its light weight and wireless connectivity. In order to increase the reliability of the system, we incorporate a face verification method which employs locally-normalized Gabor Wavelets as the features for dual verification stage. We evaluate the accuracy and processing time of the proposed face verification. It found that it produces good accuracy under limited reference sample constraint and fast response for small number of gallery images. The proposed method delivers 97%, 99.8% and 95.3% accuracy for AR, YALE B and FERET datasets. In term of processing speed, the proposed method managed to classify a single image against 500 gallery images in 1.909 seconds. The system delivers fast verification with high accuracy under the constraint of just single reference sample, which increases the reliability of the proposed system.},
   issn = {2088-5334},
   publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},
   url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1352},
   doi = {10.18517/ijaseit.7.4.1352}
}

EndNote

%A Kamaru Zaman, Fadhlan Hafizhelmi
%A Sulaiman, Ahmad Asari
%A Mohd Yassin, Ihsan
%A Md Tahir, Nooritawati
%A Rizman, Zairi Ismael
%D 2017
%T Development of Mobile Face Verification Based on Locally Normalized Gabor Wavelets
%B 2017
%9 face recognition; Gabor wavelets; local approach; single sample; verification system
%! Development of Mobile Face Verification Based on Locally Normalized Gabor Wavelets
%K face recognition; Gabor wavelets; local approach; single sample; verification system
%X In this paper, we present a mobile face verification framework for automated attendance monitoring as a solution for more efficient, portable and cost-effective attendance monitoring systems. We use Raspberry Pi as mobile embedded input module connecting the webcam and radio frequency identification (RFID) reader to the personal computer (PC) which provides mobility due to its light weight and wireless connectivity. In order to increase the reliability of the system, we incorporate a face verification method which employs locally-normalized Gabor Wavelets as the features for dual verification stage. We evaluate the accuracy and processing time of the proposed face verification. It found that it produces good accuracy under limited reference sample constraint and fast response for small number of gallery images. The proposed method delivers 97%, 99.8% and 95.3% accuracy for AR, YALE B and FERET datasets. In term of processing speed, the proposed method managed to classify a single image against 500 gallery images in 1.909 seconds. The system delivers fast verification with high accuracy under the constraint of just single reference sample, which increases the reliability of the proposed system.
%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1352
%R doi:10.18517/ijaseit.7.4.1352
%J International Journal on Advanced Science, Engineering and Information Technology
%V 7
%N 4
%@ 2088-5334

IEEE

Fadhlan Hafizhelmi Kamaru Zaman,Ahmad Asari Sulaiman,Ihsan Mohd Yassin,Nooritawati Md Tahir and Zairi Ismael Rizman,"Development of Mobile Face Verification Based on Locally Normalized Gabor Wavelets," International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 4, pp. 1198-1205, 2017. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.7.4.1352.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Kamaru Zaman, Fadhlan Hafizhelmi
AU  - Sulaiman, Ahmad Asari
AU  - Mohd Yassin, Ihsan
AU  - Md Tahir, Nooritawati
AU  - Rizman, Zairi Ismael
PY  - 2017
TI  - Development of Mobile Face Verification Based on Locally Normalized Gabor Wavelets
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 7 (2017) No. 4
Y2  - 2017
SP  - 1198
EP  - 1205
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - face recognition; Gabor wavelets; local approach; single sample; verification system
N2  - In this paper, we present a mobile face verification framework for automated attendance monitoring as a solution for more efficient, portable and cost-effective attendance monitoring systems. We use Raspberry Pi as mobile embedded input module connecting the webcam and radio frequency identification (RFID) reader to the personal computer (PC) which provides mobility due to its light weight and wireless connectivity. In order to increase the reliability of the system, we incorporate a face verification method which employs locally-normalized Gabor Wavelets as the features for dual verification stage. We evaluate the accuracy and processing time of the proposed face verification. It found that it produces good accuracy under limited reference sample constraint and fast response for small number of gallery images. The proposed method delivers 97%, 99.8% and 95.3% accuracy for AR, YALE B and FERET datasets. In term of processing speed, the proposed method managed to classify a single image against 500 gallery images in 1.909 seconds. The system delivers fast verification with high accuracy under the constraint of just single reference sample, which increases the reliability of the proposed system.
UR  - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1352
DO  - 10.18517/ijaseit.7.4.1352

RefWorks

RT Journal Article
ID 1352
A1 Kamaru Zaman, Fadhlan Hafizhelmi
A1 Sulaiman, Ahmad Asari
A1 Mohd Yassin, Ihsan
A1 Md Tahir, Nooritawati
A1 Rizman, Zairi Ismael
T1 Development of Mobile Face Verification Based on Locally Normalized Gabor Wavelets
JF International Journal on Advanced Science, Engineering and Information Technology
VO 7
IS 4
YR 2017
SP 1198
OP 1205
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 face recognition; Gabor wavelets; local approach; single sample; verification system
AB In this paper, we present a mobile face verification framework for automated attendance monitoring as a solution for more efficient, portable and cost-effective attendance monitoring systems. We use Raspberry Pi as mobile embedded input module connecting the webcam and radio frequency identification (RFID) reader to the personal computer (PC) which provides mobility due to its light weight and wireless connectivity. In order to increase the reliability of the system, we incorporate a face verification method which employs locally-normalized Gabor Wavelets as the features for dual verification stage. We evaluate the accuracy and processing time of the proposed face verification. It found that it produces good accuracy under limited reference sample constraint and fast response for small number of gallery images. The proposed method delivers 97%, 99.8% and 95.3% accuracy for AR, YALE B and FERET datasets. In term of processing speed, the proposed method managed to classify a single image against 500 gallery images in 1.909 seconds. The system delivers fast verification with high accuracy under the constraint of just single reference sample, which increases the reliability of the proposed system.
LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=1352
DO  - 10.18517/ijaseit.7.4.1352