Feature Extraction of Hand-Vein Patterns Based on Ridgelet Transform and Local Interconnection Structure Neural Network

In this paper, we propose a multiscale feature extraction method of hand-vein patterns based on ridgelet transform and local interconnection structure neural networks. In order to restrain the noises and emphasize the hand-vein pattern in the image, we perform the multiscale self-adaptive enhancement transform based on the ridgelet transform to the hand-vein image. A neural network with local interconnection structure is designed to extract the features of the hand-vein patterns and deal with different size hand-vein patterns by using different receptive fields. By using the structural matching method we identify the hand-vein patterns. Our experimental results show that the proposed methods are superior to other methods and efficiently solve the problem of extracting features from the unclear images. But more experiments using a large database are need.