%0 Journal Article %1 rreenarose2011improving %A R. Reena Rose, A. Suruliandi %B 3 %D 2011 %E Das, Vinu V %I The Association of Copmuter Electronics and Electrical Engineers %J International Journal on Network Security %K chi-square_statistic face_recognition %N 2 %P 5 %T Improving Performance of Texture Based Face Recognition Systems by Segmenting Face Region %U http://doi.searchdl.org/01.IJNS.2.3.165 %V 1 %X Textures play an important role in recognition of images. This paper investigates the efficiency of performance of three texture based feature extraction methods for face recognition. The methods for comparative study are Grey Level Co_occurence Matrix (GLCM), Local Binary Pattern (LBP) and Elliptical Local Binary Template (ELBT). Experiments were conducted on a facial expression database, Japanese Female Facial Expression (JAFFE). With all facial expressions LBP with 16 vicinity pixels is found to be a better face recognition method among the tested methods. Experimental results show that classification based on segmenting face region improves recognition accuracy.

@article{rreenarose2011improving, abstract = {Textures play an important role in recognition of images. This paper investigates the efficiency of performance of three texture based feature extraction methods for face recognition. The methods for comparative study are Grey Level Co_occurence Matrix (GLCM), Local Binary Pattern (LBP) and Elliptical Local Binary Template (ELBT). Experiments were conducted on a facial expression database, Japanese Female Facial Expression (JAFFE). With all facial expressions LBP with 16 vicinity pixels is found to be a better face recognition method among the tested methods. Experimental results show that classification based on segmenting face region improves recognition accuracy. }, added-at = {2012-09-25T08:55:17.000+0200}, author = {R. Reena Rose, A. Suruliandi}, biburl = {https://www.bibsonomy.org/bibtex/24572a8b3c621307afbc3294035b7e5ec/ideseditor}, editor = {Das, Vinu V}, interhash = {a6a049a9c12f9a9b5bd70f974be1ec6f}, intrahash = {4572a8b3c621307afbc3294035b7e5ec}, journal = {International Journal on Network Security}, keywords = {chi-square_statistic face_recognition}, month = {july}, number = 2, organization = {Institute of Doctors Engineers and scientist(IDES)}, pages = 5, publisher = {The Association of Copmuter Electronics and Electrical Engineers}, series = 3, timestamp = {2012-09-25T08:55:17.000+0200}, title = {Improving Performance of Texture Based Face Recognition Systems by Segmenting Face Region }, url = {http://doi.searchdl.org/01.IJNS.2.3.165}, volume = 1, year = 2011 }