Image matching method with illumination robustness

doi:10.11772/j.issn.1001-9081.2018061210

Journal of Computer Applications ›› 2019, Vol. 39 ›› Issue (1): 262-266.DOI: 10.11772/j.issn.1001-9081.2018061210

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Image matching method with illumination robustness

WANG Yan¹, LYU Meng², MENG Xiangfu³, LI Yuhao²

1. School of Mechanical Engineering, Liaoning Technical University, Fuxin Liaoning 123000, China;
2. Faculty of Electrical and Control Engineering, Liaoning Technical University, Huludao Liaoning 125105, China;
3. School of Electronic and Information Engineering, Liaoning Technical University, Huludao Liaoning 125105, China

Received:2018-06-12 Revised:2018-07-25 Online:2019-01-10 Published:2019-01-21
Supported by:
This work is partially supported the Surface Program of National Natural Science Foundation of China (61772249), the Natural Science Foundation of Liaoning Province (20170540418).

具有光照鲁棒的图像匹配方法

王焱¹, 吕猛², 孟祥福³, 李宇浩²

1. 辽宁工程技术大学机械工程学院, 辽宁阜新 123000;
2. 辽宁工程技术大学电气与控制工程学院, 辽宁葫芦岛 125105;
3. 辽宁工程技术大学电子与信息工程学院, 辽宁葫芦岛 125105

通讯作者: 吕猛
作者简介:王焱(1970-),女,辽宁阜新人,教授,博士,主要研究方向:图像处理、嵌入式系统;吕猛1994-),男,安徽利辛人,硕士研究生,主要研究方向:图像处理、嵌入式系统;孟祥福(1981-),男,辽宁葫芦岛人,副教授,博士,主要研究方向:Web数据库查询、空间数据分析;李宇浩(1997-),男,宁夏银川人,主要研究方向:嵌入式系统。
基金资助:
国家自然科学基金面上项目（61772249）；辽宁省自然科学基金资助项目（20170540418）。

Abstract

Abstract: Focusing on the problem that current image matching algorithm based on local feature has low correct rate of illumination change sensitive matching, an image matching algorithm with illumination robustness was proposed. Firstly, a Real-Time Contrast Preserving decolorization (RTCP) algorithm was used for grayscale image, and then a contrast stretching function was used to simulate the influence of different illumination transformation on image to extract feature points of anti-illumination transformation. Finally, a feature point descriptor was established by using local intensity order pattern. According to the Euclidean distance of local feature point descriptor of image to be matched, the Euclidean distance was determined to be a pair matching point. In open dataset, the proposed algorithm was compared with Scale Invariant Feature Transform (SIFT) algorithm, Speeded Up Robust Feature (SURF) algorithm, the "wind" (KAZE) algorithm and ORB (Oriented FAST and Rotated, BRIEF) algorithm in matching speed and accuracy. The experimental results show that with the increase of image brightness difference, SIFT algorithm, SURF algorithm, the "wind" algorithm and ORB algorithm reduce matching accuracy rapidly, and the proposed algorithm decreases matching accuracy slowly and the accuracy is higher than 80%. The proposed algorithm is slower to detect feature points and has a higher descriptor dimension, with an average time of 23.47 s. The matching speed is not as fast as the other four algorithms, but the matching quality is much better than them. The proposed algorithm can overcome the influence of illumination change on image matching.

Key words: image matching, illumination robustness, color-to-gray conversion, contrast stretching function, local intensity order pattern

摘要： 针对现有的基于局部特征的图像匹配算法对光照变化敏感、匹配正确率低等问题，提出一种具有光照鲁棒性的图像匹配算法。首先使用实时对比保留去色（RTCP）算法灰度化图像，然后利用对比拉伸函数模拟不同光照变换对图像的影响从而提取抗光照变换特征点，最后采用局部强度顺序模式建立特征点描述符，根据待匹配图像局部特征点描述符的欧氏距离判断是否为成对匹配点。在公开数据集上，所提算法与尺度不变特征变换（SIFT）算法、加速鲁棒特征（SURF）算法、"风"（KAZE）算法和ORB算法在匹配速度和匹配正确率上进行了对比实验。实验结果表明：随着图像亮度差异的增加，SIFT算法、SURF算法、"风"（KAZE）算法和ORB算法匹配正确率下降迅速，所提算法下降缓慢并且正确率均高于80%；所提算法特征点检测较慢和描述符维数较高，平均耗时为23.47 s，匹配速度不及另外四种算法，但匹配质量却远超过它们。对实时性要求不高的系统中，所提算法可以克服光照变化对图像匹配造成的影响。

关键词: 图像匹配, 光照鲁棒性, 图像灰度化, 对比拉伸函数, 局部强度顺序模式

CLC Number:

TP391.413

WANG Yan, LYU Meng, MENG Xiangfu, LI Yuhao. Image matching method with illumination robustness[J]. Journal of Computer Applications, 2019, 39(1): 262-266.

王焱, 吕猛, 孟祥福, 李宇浩. 具有光照鲁棒的图像匹配方法[J]. 计算机应用, 2019, 39(1): 262-266.

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Image matching method with illumination robustness

具有光照鲁棒的图像匹配方法

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