吉林大学学报（理学版）2018，Vol.56Issue(3)：639-644,6.DOI:10.13413/j.cnki.jdxblxb.2018.03.28
基于SIFT的车标识别算法
Vehicle Logo Recognition Algorithm Based on SIFT
摘要
Abstract
Aiming at the problems that the matching threshold was difficult and the recognition speed was slow in the process of vehicle-logo recognition ,we proposed a vehicle-logo recognition algorithm based on feature matching of scale invariant feature transformation (SIFT ) .The SIFT operator was used to extract the invariant features of the image ,such as viewing angle ,translation ,radiation , brightness and rotation , and the BP neural network algorithm was used to autonomously select vehicle-logo image features for classification ,matching and recognition .The results of simulation experiment show that the mean values of recognition rate for simple vehicle-logos and complex vehicle-logos are all more than 90% ,the algorithm has faster recognition speed and higher recognition rate ,w hich can meet the needs of practical application .关键词
车标识别/尺度不变特征变换/特征匹配/BP神经网络Key words
vehicle-logo recognition/scale invariant feature transformation (SIFT )/feature matching/BP neural network分类
信息技术与安全科学引用本文复制引用
耿庆田,于繁华,王宇婷,赵宏伟,赵东..基于SIFT的车标识别算法[J].吉林大学学报（理学版）,2018,56(3):639-644,6.基金项目
吉林省产业创新专项基金(批准号:2016C078)、吉林省产业技术研究与开发专项基金(批准号:2017C031-2)和吉林省教育厅"十三五"科学技术研究项目(批准号:2018269). （批准号:2016C078）
