Efficient normalized cross correlation calculation method for stereo vision based robot navigation  

作　　者：Yehu SHEN 

机构地区：[1]Department of System Integration and IC Design, Suzhou Institute of Nano-tech and Nano-bionics, Chinese Academy of Sciences, Suzhou 215125, China

出　　处：《Frontiers of Computer Science》2011年第2期227-235,共9页中国计算机科学前沿（英文版）

摘　　要：Stereo vision systems are widely used for autonomous robot navigation. Most of them apply local window based methods for real-time purposes. Normalized cross correlation （NCC） is notorious for its high computational cost, though it is robust to different illumination conditions between two cameras. It is rarely used in real-time stereo vision systems. This paper proposes an efficient normalized cross correlation calculation method based on the integral image technique. Its computational complexity has no relationship to the size of the matching window. Experimental results show that our algorithm can generate the same results as traditional normalized cross correlation with a much lower computational cost. Our algorithm is suitable for planet rover navigation.Stereo vision systems are widely used for autonomous robot navigation. Most of them apply local window based methods for real-time purposes. Normalized cross correlation （NCC） is notorious for its high computational cost, though it is robust to different illumination conditions between two cameras. It is rarely used in real-time stereo vision systems. This paper proposes an efficient normalized cross correlation calculation method based on the integral image technique. Its computational complexity has no relationship to the size of the matching window. Experimental results show that our algorithm can generate the same results as traditional normalized cross correlation with a much lower computational cost. Our algorithm is suitable for planet rover navigation.

关 键 词：normalized cross correlation （NCC） stereo matching integral image 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TP242.6[自动化与计算机技术—计算机科学与技术]