摘要
针对现有车型识别的准确性和实时性不能同时满足要求的问题,提出了复合的图像匹配模型与识别方法.先应用Harris角点对车型初分类,再应用SIFT特征进行细分类,该方法与只利用SIFT特征进行识别的方法相比,在保证识别准确性基本不变的情况下,处理时间减少了近2/3,实时性得到较大改善.
Considering to the important factors of accuracy and real-time performance can not meet the require- ment simultaneously in current vehicle recognition, a compound image matching model and a recognition method were developed, namely classifying vehicles firstly by utilizing Harris comer, then classifying vehicles detailedly by using SIFT feature. Compared with the one used SIFT feature only, the method shortens the time of disposal by 2/ 3 under guaranteeing the accuracy to be kept essentially constant, real-time performance was improved greatly.
出处
《哈尔滨理工大学学报》
CAS
2012年第3期69-73,共5页
Journal of Harbin University of Science and Technology
基金
黑龙江省交通运输厅重点项目(201000005)
