 Gender Classification using Face Images: A Review Dhanashri P. Lale Department of Electronics and Telecommunication Engineering, SKN Sinhgad college of Engineering, Pandharpur Tal- Pandharpur. Dist- Solapur. State- Maharashtra. India. Pin code- 413304 Kailash J. Karande Department of Electronics and Telecommunication Engineering, SKN Sinhgad college of Engineering, Pandharpur Tal- Pandharpur. Dist- Solapur. State- Maharashtra. India. Pin code- 413304 Abstract— In field of Image processing face is one of the most important biometric traits and is becoming more popular for the security purpose in now a days. During past several years classification of gender from facial images has gained enormous significance and has become a popular area of research. Many researches have done on the gender classification from several years. Still, this is a very important field of image processing because of its applications in many areas like monitoring, surveillance, commercial profiling and human-computer interaction. Security applications have high importance in this area. Gender classification using facial and racial features can be used as part of a face recognition process. This paper comparison of different gender classification techniques and use of different racial features such as eyes, nose, mouth etc. for gender classification. Keywords—Gender Classification; facial and racial features extraction. I. INTRODUCTION Identifying gender, age and ethnicity of human faces [7] using computer has been popular and gaining immense attention in past several years. These attributes such as gender, age, and ethnicity can play an important role in many applications such as human-computer interaction, surveillance, content-based indexing and searching, biometrics, demographic studies and targeted advertising. Studies have shown that a human can easily differentiate between a male and female but, it is a difficult for machine. There exist some distinguishable features between male and female which are used by machine to classify gender. Gender recognition is a pattern recognition problem [14]. Pattern recognition can be divided into two parts, one and two stage pattern recognition systems. One stage pattern recognition system classifies input data directly. Two stage pattern recognition systems consist of feature extractor, with classifier. In addition to facial features, racial features such as eyes, nose, mouth etc. are also used for gender classification. In artificial intelligence image processing and machine learning plays an very important role and perform difficult jobs such as face recognition, gesture recognition, facial expression recognition and gender classification [9]. Some applications should not require the physical contact or attention of human being. But some applications require human attention or physical contact. Human parts such as iris, hand or fingerprint would require some cooperation from the human and thus limit its applicability. Whereas face is the most acceptable biometric trait than others because it is easily approachable to the machine therefore large no of application areas are identified where gender recognition is very much involved [2]. International Journal of Latest Trends in Engineering and Technology (IJLTET) ISSN: 2278-621X 333 Vol 7 issue 2 July 2016 http://dx.doi.org/10.21172/1.72.553