A hand vein authentication system in which the identity of an individual can be readily confirmed upon gripping a handle is proposed. This recognition method incorporates infrared light-emitting diode (LED) onto a door handle and sets a charge-coupled device (CCD) camera on the other side of the hand. It builds on fuzzy c-means clustering and parallel neural networks (NNs); moreover, it is expected to solve the pattern recognition problem in large-scale databases using NNs due to its self-learning and parallel processing capabilities and by effectively incorporating training patterns. The experimental results validate the e±ciency of the proposed algorithm.

This letter presents an automatic surveillance system using fish-eye lens camera. Our system achieves wide-area automatic surveillance without a dead angle using only one camera. We propose a new human detection method to select the most adaptive classifier based on the locations of the human candidates. Human regions are detected from the fish-eye image effectively and are corrected for perspective versions. An experiment is performed on indoor video sequences with different illumination and crowded conditions, with results demonstrating the efficiency of our algorithm.

运用Noll建议的Zernike多项式形式表征经大气扰动的波面，求出由两个离焦面上的光强分布决定的Zernike多项式的前n项在特定的探测器上的响应矩阵R.由R和输入的随机波面在两个离焦面上的光强分布，可方便地求出其Zernike多项式的系数，从而实现了波前的探测和重构.采用光线追迹的方法，用计算机模拟验证了这种方法的原理和可行性.