Automatic gender determination received many attentions in the recent years due to its potential applications in e-commerce and demographic data collection. Face and voice are the most common factors of human which are used to determine the gender. A comparative study of gender recognition based hand-crated and deep features via ear images is introduced in this paper. The EarVN1.0 dataset is employed to evaluate this study. The experimental results show that deep learning approach clearly outperforms features-based methods for gender determination based on ear images.