This paper proposes a robust approach for face detection and gender
classification in color images. Previous researches about gender recognition
suppose an expensive computational and time-consuming pre-processing step in
order to alignment in which face images are aligned so that facial landmarks
like eyes, nose, lips, chin are placed in uniform locations in image. In this
paper, a novel technique based on mathematical analysis is represented in three
stages that eliminates alignment step. First, a new color based face detection
method is represented with a better result and more robustness in complex
backgrounds. Next, the features which are invariant to affine transformations
are extracted from each face using scale invariant feature transform (SIFT)
method. To evaluate the performance of the proposed algorithm, experiments have
been conducted by employing a SVM classifier on a database of face images which
contains 500 images from distinct people with equal ratio of male and female
