一种新型神经网络景像匹配算法

A New Scene Matching Algorithm Based on Neural Network

本文给出了一种基于二层前向神经网络的景像匹配算法。神经网络的权值与匹配定位参数相对应,通过训练求出网络权值,从而确定匹配定位参数。由于网络的学习算法采用了递推计算,大大减小了权值计算的存储量;同时其为二阶算法,避免权值的训练陷入局部极小点,收敛速度较快,精度高。仿真结果表明其精度和匹配速度均优于最小二乘匹配算法。

A two layers forward neural network based scene matching algorithm is proposed in this paper.The weight values of the neural network are correspondence with the positioning parameters.The weight values of the network are calculated by training.Then the positioning parameters are got.By using recursive calculation,the storage quantity of the learning algorithm is reduced greatly.The new matching algorithm is a second-order algorithm,so it is avoided to trap into local minimum.The new algorithm converges rapidly and has high precision.The simulation results show that the precision and the matching rate of the new matching algorithm are better than that of the least square matching algo- rithm.