基于改进遗传神经网络的人脸识别算法研究

Study on Face Recognition Algorithm Based on Improved Genetic Neural Network

以人脸识别系统作为主要研究内容,提出了基于改进遗传神经网络的人脸识别算法,然后以人脸数据库中的灰度图像作为训练对象,并实现了相应的人脸特征信息的提取。分析了全面表达神经元运算机理的神经元数学模型;研究了BP算法对神经网络指导式的学习规则,并建立了相应的数学模型;应用ORL人脸数据库进行仿真验算,证明了基于改进遗传神经网络的人脸识别算法的可行性;为精确识别人脸特征信息并建立人脸特征信息模型提出了一种新的研究思路。

Taking face recognition system as the main research content, this paper put forward face recognition algorithm based on improved genetic neural network, and then took gray level images in the face database as the training objects, and realized the extraction of corresponding face feature information. It analyzed mathematical model of neurons which completely expresses neuron operation mechanism,studied the learning rules of BP Algorithm on the neural network guidance formula, and established corresponding mathematical model. It conducted simulation check calculation with ORL face data- base, proving the feasibility of face recognition algorithm based on improved genetic neural network, putting forward a new research idea to accurately identify the face feature information, and establishing the face feature information model.