摘要
在基于线阵CCD相机的汽车底盘图像对比和安全检测中,特征点匹配算法是项目研究重点,但是大多数现存的方法不能满足项目对匹配数量、质量和分布的要求.基于SURF(speeded-up robust features)算法,并引入显著性约束和形变约束过滤掉错误匹配,最终获得数量与质量显著提高的匹配集合.结果实验结果表明,该方法获得的纵向分布完成系数大于80%、误匹配率低于2%,基本到达了安全检测的要求.
The algorithm of feature matching is the focus of research of image contrast and safety detection for the automobile chassis based on linear CCD camera.but most available methods fail to achieve satisfying quantitative,qualitative.Distributed matches simultaneously.This paper introduced saliency constraints and deformation constraints to filter out mismatches based on SURF(speeded-up robust features)algorithm,and finally obtained matching sets with significantly improved quantity and quality.The experimental results showed that the vertical distribution completion coefficient obtained by this method was more than 80%,and the mismatch rate was less than 2%,which basically met the requirements of security detection.
作者
刘文华
陈志宏
LIU Wen-hua;CHEN Zhi-hong(School of Information Engineering,Zhangzhou Institute of Technology,Zhangzhou 363000,China;Zhangzhou Eastern Intelligent Meter Co.,Ltd,Zhangzhou 363000,China)
出处
《哈尔滨商业大学学报(自然科学版)》
CAS
2019年第6期693-699,共7页
Journal of Harbin University of Commerce:Natural Sciences Edition
基金
漳州市重大科技专项项目(ZZ2017ZD04)