Fingerprint Ridge Orientation Estimation Based on Neural Network

Ridge orientation is one of the fundamental features of a fingerprint image. Orientation estimation serves for feature extraction and matching and is the base of fingerprint recognition. Most existing orientation estimation methods are based on the characteristic of pixel intensity in a block. This paper uses neural network to learn the ridge orientation. The trained network has the property of responding to true ridge orientation with a large value and responding to the false ridge orientation with a small value. When estimating fingerprint ridge orientation, the responded values to each orientation at each image block are used to compute the fingerprint orientation field. The proposed method turns out more robust than the existing method. Key-Words: Fingerprint recognition, Ridge orientation, Neural network, Filtering, Orientation setection