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[1]李旋,韩天园,吕凯光,等.基于改进SIFT算法的交通事故图像匹配*[J].中国安全生产科学技术,2021,17(1):182-188.[doi:10.11731/j.issn.1673-193x.2021.01.029]
　LI Xuan,HAN Tianyuan,LYU Kaiguang,et al.Images matching of traffic accident based on improved SIFT algorithm[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2021,17(1):182-188.[doi:10.11731/j.issn.1673-193x.2021.01.029]
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基于改进SIFT算法的交通事故图像匹配*
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
17
期数:
2021年1期
页码:
182-188
栏目:
职业安全卫生管理与技术
出版日期:
2021-01-31

文章信息/Info

Title:
Images matching of traffic accident based on improved SIFT algorithm
文章编号:
1673-193X(2021)-01-0182-07
作者:
李旋; 韩天园; 吕凯光; 刘永涛
(长安大学 汽车学院，陕西 西安 710064)
Author(s):
LI Xuan;  HAN Tianyuan;  LYU Kaiguang;  LIU Yongtao
(School of Automobile,Chang’an University,Xi’an Shaanxi 710064,China)
关键词:
交通事故; 尺度不变特征变换; 改进的高斯金字塔; 局部线性嵌入; 分区域特征点匹配
Keywords:
traffic accident;  scaleinvariant feature transformation;  improved Gaussian pyramid;  local linear embedding;  regional feature point matching
分类号:
X951
DOI:
10.11731/j.issn.1673-193x.2021.01.029
文献标志码:
A
摘要:
为解决无人机航拍交通事故现场图像特征点数量较少、匹配成功率较低、耗时过长的问题，提出1种改进的SIFT算法，使用Gabor滤波对图像进行特征提取，基于改进的高斯金字塔和多方向多尺度Gabor频谱特点提取出具有尺度、旋转不变性的特征点，结合LLE算法对特征描述符进行降维处理，通过DBSCAN算法对特征点进行密度聚类，计算区域内的特征点距离的梯度下降一致性程度，结合蚁群算法判断特征点是否匹配成功。结果表明：改进的SIFT算法无论是在匹配精度还是在匹配效率上都优于同类算法，证明提出算法的有效性。
Abstract:
In order to solve the problems of small number of feature points,low matching success rate and long timeconsuming for the UAC aerial field images of traffic accidents,an improved SIFT algorithm was proposed.The Gabor filter was used to extract the image features,and the feature points with the scale and rotation invariance were extracted based on the improved Gaussian pyramid and multidirectional multiscale Gabor spectrum features.The dimension reduction of feature descriptors was carried out combining with LLE algorithm,and the density clustering of feature points was conducted through the DBSCAN algorithm.The consistency degree of gradient descent for the distances of feature points in the region was calculated,and the ant colony algorithm was applied to determine whether the feature points were matched successfully.The results showed that the improved SIFT algorithm was superior to similar algorithms in both matching accuracy and matching efficiency,which proved the effectiveness of the proposed algorithm.

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备注/Memo

备注/Memo:

* 基金项目： 陕西省重点研发计划项目（2020ZDLGY16-08）；中央高校基本科研业务费专项资金项目（300102220111，300102229668）
作者简介： 李旋，硕士研究生，主要研究方向为交通事故与图像处理。
通信作者： 刘永涛，博士，副教授，主要研究方向为交通事故与图像处理。
更新日期/Last Update: 2021-02-04