Development of Mobile Face Verification Based on Locally Normalized Gabor Wavelets

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...

Full description

Bibliographic Details
Main Authors: Rizman, Z.I (Author), Sulaiman, A.A (Author), Tahir, N.M (Author), Yassin, I.M (Author), Zaman, F.H.K (Author)
Format: Article
Language:English
Published: Insight Society 2017
Subjects:
Online Access:View Fulltext in Publisher
View in Scopus
LEADER 02373nam a2200253Ia 4500
001 10.18517-IJASEIT.7.1.1352
008 220120s2017 CNT 000 0 und d
020 |a 20885334 (ISSN) 
245 1 0 |a Development of Mobile Face Verification Based on Locally Normalized Gabor Wavelets 
260 0 |b Insight Society  |c 2017 
520 3 |a 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 a 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. © 2017, International Journal on Advanced Science, Engineering and Information Technology. All Rights Reserved. 
650 0 4 |a face recognition 
650 0 4 |a Gabor wavelets 
650 0 4 |a local approach 
650 0 4 |a single sample 
650 0 4 |a verification system 
700 1 0 |a Rizman, Z.I.  |e author 
700 1 0 |a Sulaiman, A.A.  |e author 
700 1 0 |a Tahir, N.M.  |e author 
700 1 0 |a Yassin, I.M.  |e author 
700 1 0 |a Zaman, F.H.K.  |e author 
773 |t International Journal on Advanced Science, Engineering and Information Technology  |x 20885334 (ISSN)  |g 7 4, 1198-1205 
856 |z View Fulltext in Publisher  |u https://doi.org/10.18517/IJASEIT.7.1.1352 
856 |z View in Scopus  |u https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121003203&doi=10.18517%2fIJASEIT.7.1.1352&partnerID=40&md5=a260af591de56c3553ad58decab75dea