Singular Points Detection Based on Zero-Pole Model in Fingerprint Images

An algorithm is proposed, which combines Zero-pole Model and Hough Transform (HT) to detect singular points. Orientation of singular points is defined on the basis of the Zero-pole Model, which can further explain the practicability of Zero-pole Model. Contrary to orientation field generation, detection of singular points is simplified to determine the parameters of the Zero-pole Model. HT uses rather global information of fingerprint images to detect singular points. This makes our algorithm more robust to noise than methods that only use local information. As the Zero-pole Model may have a little warp from actual fingerprint orientation field, Poincare index is used to make position adjustment in neighborhood of the detected candidate singular points. Experimental results show that our algorithm performs well and fast enough for real-time application in database NIST-4.