In this study, a singular points detection method based on low-resolution image processing technique and Poincare index algorithm was introduced. First, 2D discrete wavelet transform (DWT) was used to conduct fingerprint image operation, then a LL-band image that has 1∕4 resolution of the original image was obtained to reduce the operation needed in the subsequent processing. After finishing the detection procedure of singular point, each possible singular point was taken as the center to calculate the local binary pattern (LBP) features at its peripheral as reference standard for selecting correct singular point. Through this way, fake singular point is removed. The experimental result shows that the method in this study could indeed reduce the chance to detect fake singular points due to noise effect. Meanwhile, the processing speed of the traditional Poincare index method can be speeded up.
Ching-Han Chen, Ching-Yi Chen, Tsung-Min Hsu, "Singular Points Detection in Fingerprints Based on Poincare Index and Local Binary Patterns" in Journal of Imaging Science and Technology, 2019, pp 030401-1 - 030401-7, https://doi.org/10.2352/J.ImagingSci.Technol.2019.63.3.030401