A New Image Matching Algorithm Based on Improved SURF Operator

ZHANG Pei; GUO Hui; LIU Fang-hui; HU Fang-shang; ZHOU Shao-ping

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A New Image Matching Algorithm Based on Improved SURF Operator

更新时间：2026-09-04

- A New Image Matching Algorithm Based on Improved SURF Operator
- Vol. 34, Issue 7, Pages: 96-100(2017)
- 作者机构：
  
  华东理工大学机械与动力工程学院,上海,200237
- 作者简介：
- 基金信息：
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- Published：2017
- 稿件说明：
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张培, 郭慧, 刘芳辉, 胡方尚, 周邵萍. 一种基于改进SURF算子的印刷品图像匹配算法[J]. 微电子学与计算机, 2017, 34(7): 96-100.

ZHANG Pei, GUO Hui, LIU Fang-hui, et al. A New Image Matching Algorithm Based on Improved SURF Operator[J]. 2017, 34(7): 96-100.
张培, 郭慧, 刘芳辉, 胡方尚, 周邵萍. 一种基于改进SURF算子的印刷品图像匹配算法[J]. 微电子学与计算机, 2017, 34(7): 96-100. DOI：

ZHANG Pei, GUO Hui, LIU Fang-hui, et al. A New Image Matching Algorithm Based on Improved SURF Operator[J]. 2017, 34(7): 96-100. DOI：

摘要

针对传统算法精度低、速度慢的问题

提出一种改进的SURF算法.算法采用一种全新的Harr-like特征描述符

增加有效特征点个数

提高描述子鉴别力

同时结合BBF搜索方法

提升匹配速度.实验表明

与原有SURF算法相比

改进算法的匹配点对数增加了15%以上

同时提高了速度.算法的改善为图像匹配技术在印刷行业的应用开拓了更广阔的前景.

Abstract

Aiming at the problem of low precision and slow speed of traditional algorithms

this paper proposes an improved SURF algorithm. The algorithm uses a brand new Harr-like feature descriptor to increase the number of valid feature points and improve the discriminant ability of the descriptors. At the same time we combined with BBF search method to enhance the matching speed. The experimental results show that the matching point of the improved algorithm is increased by more than 15% compared with the original SURF algorithm

and the speed is also improved. The improvement of the algorithm opens up a broader prospect for the application of image matching technology in the printing industry.

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references

李俊平. 数字印刷品的质量控制[J]. 印刷工业, 2016, 11(3): 64-65. DOI: 64

Lowe D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 2004, 60(2): 91-110. DOI: 91

Zhang Chunjie, Jing Liu, Chao Liang, et al. Image classification using Harr-like transformation of local features with coding residuals[J]. Signal Processing, 2013, 93(8): 2111-2118. DOI: 2111

尚明姝. 一种基于改进SURF的图像配准方法[J]. 微电子学与计算机, 2014, 31(2): 125-128. DOI: 125

张格森. 一种图像局部特征快速匹配算法[J]. 计算机技术与应用, 2015, 41(11): 124-127. DOI: 124

Nikolett Bereczky, Amalia Duch, Krisztián Németh, et al. Quad-kd trees: A general framework for kd trees and quad trees[J]. Theoretical Computer Science, 2016, 616: 126-140. DOI: 126

王文举, 赵萍, 陈伟, 等. 彩色印刷品缺陷快速精确检测方法研究[J]. 包装工程, 2015, 36(17): 112-130. DOI: 112

BAY H, TUYTELAARS T, Gool V L, et al. Speeded-up robust features(SURF)[J]. Computer Vision and Image Understanding, 2008, 110(3): 346-359. DOI: 346

Manish I Patel, Vishvjit K Thakar, Shishir K Shah. Image registration of satellite images with varying Illumination level using HOG descriptor based SURF[J]. Procedia Computer Science, 2016, 93: 382-388. DOI: 382

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