alexa Abstract | Face Recognition through Multi Model Image Features using GMM
ISSN ONLINE(2320-9801) PRINT (2320-9798)

International Journal of Innovative Research in Computer and Communication Engineering
Open Access

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations

700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Research Article Open Access


In many real-time face recognition systems such as e-passport, law enforcement and ID card identification, there is usually only a single sample per person (SSPP) enrolled in these systems, and many existing face recognition methods may fail to work well because there are not enough samples for discriminative feature extraction in this scenario. However, the probe samples of these face recognition systems are usually captured on the spot, and it is possible to collect multiple face images per person for on-location probing, which is potentially useful to improve the recognition performance. In this paper, we propose a method based on locality repulsion projections (LRP) and Histograms to address the problem of SSPP face recognition using Multiple Sample per Person (MSPP). The LRP method is motivated by our observation that similar face images from different people may lie in a locality in the feature space and cause misclassifications. We propose the method with the aim of separating the samples of different classes within a neighbor hood through GMM for easier classification. To better characterize the similarity between each gallery face and the probe image set, we propose a GMM method for assigning a label to each probe image set. Finally, we measure the similarity between the images using Euclidean distance formulae.

To read the full article Peer-reviewed Article PDF image | Peer-reviewed Full Article image

Author(s): L.Gunasekaran, S.P.Maniraj, J.Jegadeesan

Share This Page

Additional Info

Loading Please wait..
Peer Reviewed Journals
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version