A Fuzzy Classifier using Bank of Gabor Filters to Facial Images’ Gender Classification

This paper explores a design-based method to use Gabor filter features and fuzzy system for improved texture recognition. In this article, we will present an unsupervised approach for facial image gender classification based on texture features. This system is 1-input, 1-output Mamdani type one, applies facial texture properties as inputs and reveals the probability of being male face image in output. Choosing proper threshold value, the decision about gender is made. 85.5% obtained classification rate prove the efficiency of proposed method.

کلیدواژه ها:

Gender classification ، Fuzzy inference system ، Gabor Filter