Deep learning for hand segmentation in complex backgrounds

Abstract

This paper presents a Deep Learning segmentation approach for hand segmentation in gray level images with cluttered backgrounds where standard techniques cannot be used. Two networks were trained with a database of hand images derived from widely used palmprint image databases, Hong Kong Polytechnic University (HKPU) and Chinese Academy of Science (CASIA). The image dataset is augmented with complex patterns and used to train and test the Neural Networks, providing promising results.