Open Access Open Access  Restricted Access Subscription Access

Face Recognition using Genetic Algorithm with Self-Organizing Mapping based Dimensionality Reduction Technique

Md. Rabiul Islam

Abstract


The contribution of this work is to develop a face recognition technique where Genetic Algorithm has been used. Here facial features are extracted using Active Appearance Model (AAM) and Kohonen Self-Organizing Mapping (SOM) technique has applied to reduce the dimension of the extracted features. Efficient image pre-processing techniques are used to prepare the face for the proposed system. Finally, Genetic Algorithm has been used to classify the facial features. In GA, various operators have been applied to optimize the performance of the proposed face recognition system. Valid standard dataset has been used to measure the performance of the proposed system. Experimental results and performance analysis shows the superiority of the proposed system in various dimensions.

Keywords: Face recognition, person identification system, kohonen self-organizing mapping technique, active appearance model, genetic algorithm

Cite this Article:

Rabiul Islam. Face recognition Using Genetic Algorithm with Self-Organizing Mapping Based Dimensionality Reduction Technique. Journal of Multimedia Technology & Recent Advancements. 2015; 2(1): 22–26p.


Full Text:

PDF

References


Dominique Ginhac, Fan Yang, Xiaojuan Liu, et al. Robust face recognition system based on a multi-views face database. In Recent Advances in Face Recognition. 2008; 27–38p.

Samal A, Iyengar PA. Automatic recognition and analysis of human faces and facial expressions: a survey. Patt. Recogn. 1992; 25(1): 65–77p.

Valentin D, Abdi H, Toole AJO. Connectionist models of face processing: a survey. Patt. Recogn. 1994; 27(9): 1209–1230p.

Chellappa R, Wilson CL, Sirohey S. Human and machine recognition of faces: a survey. Proc. IEEE. 1995; 83(5):

–740p.

Zhang J, Yan Y, Lades M. Face recognition: eigenface, elastic matching, and neural nets. Proc. IEEE. 1997; 85(9): 1423–1435p.

Craw I, Costen N, Kato T. How should we represent faces for automatic recognition? IEEE Trans. Patt. Anal. Mach. Intell. 1999; 21(8): 725–736p.

Burton AM, Bruce V, Hancock PJB. From pixels to people: a model of familiar face recognition. Cognitive Sci. 1999; 23(1): 1–31p.

Md. Rabiul Islam, Rizoan Toufiq. Face recognition approach based on genetic algorithm. International Conference on Engineering Research, Innovation and Education (ICERIE 2013), January, Sylhet, Bangladesh. 347–352p.

Md. Golam Moazzam, Md. Al-Amin Bhuiyan. A novel approach for human face detection using genetic algorithm. Journal of Electronics and Computer Science. 2009; 10.

Vimal Chand CR. Face and gender recognition using genetic algorithm and hopfield neural network. Global Journal of Computer Science and Technology. 2010; 10(1): 2–3p.

Gary G Yen, Nethrie Nithianandan. Facial feature extraction using genetic algorithm. Evolutionary Computation, CEC '02. Proceedings of the 2002 Congress on. 2002; 2: 1895–1900p.

Derya Ozkan. Feature selection for face recognition using a genetic algorithm. Documentation from Online: http:// www.cs.bilkent.edu.tr/~guvenir/courses/cs550/Workshop/Derya_Ozkan.pdf.

Stephen Milborrow, Fred Nicolls. Locating facial features with an extended active shape model. URL: http://www.milbo.org/stasm-files/locating-facial-features-with-an-extended-asm.pdf.

Herpers R, Verghese G, Derpains K, et al. Detection and tracking of face in real environments. IEEE Int. Workshop on Recognition, Analysis and Tracking of Face and Gesture in Real- Time Systems, Corfu, Greece, 1999; 96–104p.

Teuvo Kohonen. Self-Organizing formation of topologically correct feature maps. Biol. Cybern. 1982; 43(1): 59–69p.

Rajasekaran S, Vijayalakshmi Pal GA. Neural Networks, Fuzzy Logic, and Genetic Algorithms Synthesis and Applications. Prentice-Hall, Second Edition. 2003.


Refbacks

  • There are currently no refbacks.