Abstract: Gender classification is a binary classification system where system has to assign a given test image to one of the two classes (male or female). The gender classification system with large set of training data normally gives good accuracy. But to achieve good accuracy with small training data is a difficult task. This paper proposes an algorithm for gender classification with small training data and it gives good accuracy even with one image per person for training. The system contains mainly two parts: feature vector generation and classification. Feature vector generation is done with PCA (Principal Component Analysis ).