Local Gabor directional pattern histogram sequence (LGDPHS) for age and gender classification

This paper proposes means to classify age and gender in facial images using novel features. First, Gabor magnitude pictures are obtained by convolving the image with Gabor filters in several scale and orientation, followed by encoding with Local Directional Pattern (LDP) operator which enhances information. Then, the maps are divided into several blocks, and histograms are extracted from each block. The histograms are concatenated to a vector. Then Principal Component Analysis (PCA) is used to reduce the dimensions. Finally, the feature vector is classified by Support Vector Machine (SVM). The experimental results demonstrate that the algorithm proposed in this paper is effective method, compared to other similar methods.