Soft Computing and Face Recognition: A Survey

• Published in: Soft Computing Systems pp. 69 - 79
• Main Authors: Anil, J., Lekshmi Kanthan, Padma Suresh, Krishna Veni, S. H.
• Format: Book Chapter
• Language: English
• Published: Singapore Springer Singapore
• Series: Communications in Computer and Information Science
• Subjects: Face recognition; Fuzzy logic; Genetic algorithm; Neural networks; Pattern recognition problem; Principle component analysis; Radial basis functions; Soft computing
• ISBN: 9811319359; 9789811319358
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-981-13-1936-5_8

Soft computing has found profound application in the challenging areas like pattern recognition, classification, optimization etc. Face recognition is basically a pattern recognition problem. This paper reviews some of the efficient algorithms that uses soft computing techniques along with conventional methods like Principal Component Analysis, Radial Basis Functions etc. for face recognition. Conventional methods for pattern recognition are very efficient even without introducing soft computing techniques. But this is not the case with face recognition as it is a complex problem owing to the various challenges like illumination variation, ageing, expression changes, occlusion etc. Due to these factors face recognition becomes unpredictable and so soft computing techniques can be applied, which are very efficient in solving unpredictable and incomplete problems. Soft computing copies human mind. In other words, soft computing thinks like humans. The algorithms discussed in this paper employs various soft computing techniques like Neural networks, genetic algorithm and fuzzy logic.