Gender classification using Radon and Wavelet Transforms

In this paper a new approach is proposed to recognize gender from the face image. This approach will detect the face from the given image. Radon and Wavelet Transforms are combined to extract key facial features for each face images of male and female. These features will be used to classify the face images of each pattern. We have compared the DCT extracted face feature with our face feature extracted by Radon and Wavelet Transforms. The experimental result shows that the proposed approach (combination of face detector, radon and wavelet transforms, KNN classifier) achieves better performance.