SBIR Phase I: Robust, Intelligent and Practical Face Recognition Based on Optical Joint Transform Correlation and Neural Networks

9761141 Kim这个小型企业创新研究第一阶段项目将开发一个光电人脸识别系统，其中与传统系统相关的问题，如不变识别多阶段操作、系统复杂性、高成本和大数据存储容量要求，将使用嵌入神经网络的光学联合变换相关器(JTC)来克服。这种神经网络和JTC的独特组合将不受面部表情、面部毛发、头部位置、相机比例和照明的影响，可用于各种安全应用，包括门禁系统、个人身份识别系统和其他基于生物度量签名的安全系统。

9761141 Kim This Small Business Innovation Research (SBIR) Phase I project will develop an optoelectronic face recognition system, in which problems associated with traditional systems such as invariant recognition multi-stage operation, system complexity, high cost and large data storage capacity requirements will be overcome using a neural network-embedded optical joint transform correlator (JTC). This unique combination of neural networks and JTC will be invariant to facial expression, facial hair, head position, camera scale and lighting, and can be used in a variety of security applications including access control systems, personal identification systems and other bio-metric-signature based security systems.