一种基于ORB特征的水下立体匹配方法
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摘要
针对水下环境中传统算法对双目图像匹配时存在速度慢、误匹配较多等问题,提出一种基于ORB(的特征检测和曲线极线约束相结合的水下立体匹配方法。先检测图像的特征点,生成描述子,并进行特征匹配;然后根据折射定律,结合双目相机的内外参数,推导出水下曲线极线;最后结合水下曲线极线约束,剔除误匹配点。实验结果表明,相比传统的SIFT算法与曲线约束,论文提出的立体匹配方法在有效控制误匹配的情况下,显著提高了运算速度,对提升水下双目视觉系统的快速处理能力具有实践意义。
Since the traditional algorithm may cause problems such as slow running speed and more mismatching points when perform stereo matching on underwater environment, the ORB characteristics detection and curve restriction has been applied in this paper. Firstly the image should be detected so as to find out the characteristics,generate the descriptor, and match the feature points. Then the underwater curve restriction can be deduced according to the law of refraction combining internal and external parameters of camera. Finally the mismatching points can be decreased by means of underwater curve restriction. The experimental results have shown that in the case of effectively controlling mismatches, the speed of this algorithm are faster than traditional SIFT algorithm combined with curve restriction. As a result, it is of practical significance to improve the speed of underwater binocular vision system.
Since the traditional algorithm may cause problems such as slow running speed and more mismatching points when perform stereo matching on underwater environment, the ORB characteristics detection and curve restriction has been applied in this paper. Firstly the image should be detected so as to find out the characteristics,generate the descriptor, and match the feature points. Then the underwater curve restriction can be deduced according to the law of refraction combining internal and external parameters of camera. Finally the mismatching points can be decreased by means of underwater curve restriction. The experimental results have shown that in the case of effectively controlling mismatches, the speed of this algorithm are faster than traditional SIFT algorithm combined with curve restriction. As a result, it is of practical significance to improve the speed of underwater binocular vision system.
引文
[1]Cao Z L,Yan Z H,Wang H.Summary of binocular stereo vision matching technology[J].Journal of Chongqing University of Technology(Natural Science),2015,29(2):70-75.曹之乐,严中红,王洪.双目立体视觉匹配技术综述[J].重庆理工大学学报(自然科学),2015,29(2):70-75.
[2]Zhang Q,Hao K,Li H B.Research on scale invariant feature transform feature matching based on underwater curve constraint[J].Acta Optica Sinica,2014,34(2):0215003.张强,郝凯,李海滨.水下环境中基于曲线约束的SIFT特征匹配算法研究[J].光学学报,2014,34(2):0215003.
[3]Zhang Q,Lu S Q,Li H B,et al.Research on underwater stereo matching method based on color segmentation[J].Acta Optica Sinica,2016,36(8):0815001.张强,卢士强,李海滨,等.基于色彩分割的水下立体匹配算法的研究[J].光学学报,2016,36(8):0815001.
[4]赵鹏.机器视觉研究与发展[M].北京:科学出版社,2012.
[5]Sanchez-Ferreira C,Mori J Y,Llanos C H,et al.Development of a stereo vision measurement architecture for an underwater robot[C]//2013 IEEE 4th Latin American Symposium on Circuits and Systems,2013:1-4.
[6]Lowe D G.Distinctive image features from scale-invariant keypoints[J].International Journal of Computer Vision,2004,60(2):91-110.
[7]Lowe D G.Object recognition from local scale-invariant features[C]//Proceedings of the Seventh IEEE International Conference on Computer Vision,1999,2:1150-1157.
[8]Rublee E,Rabaud V,Konolige K,et al.ORB:An efficient alternative to SIFT or SURF[C]//2011 IEEE International Conference on Computer Vision,2011:2564-2571.
[9]Peng H,Wen Y X,Zhai R F,et al.Stereo matching for binocular citrus images using SURF operator and epipolar constraint[J].Computer Engineering and Applications,2011,47(8):157-160.彭辉,文友先,翟瑞芳,等.结合SURF算子和极线约束的柑橘立体图像对匹配[J].计算机工程与应用,2011,47(8):157-160.
[10]Gedge J,Gong M L,Yang Y H.Refractive epipolar geometry for underwater stereo matching[C]//2011 Canadian Conference on Computer and Robot Vision,2011:146-152.
[11]Li J,Pan T S,Tseng K K,et al.Design of a monocular simultaneous localisation and mapping system with ORB feature[C]//2013 IEEE International Conference on Multimedia and Expo,2013:1-4.
[12]Zhang W M,Deng X X,Zhang Q,et al.Non-parallel system underwater image transformation model[J].Acta Photonica Sinica,2015,44(2):211002.张文明,邓茜雪,张强,等.基于非平行系统的水下图像转化模型[J].光子学报,2015,44(2):211002.
[13]Wang H B,Sun H Y,Shen J,et al.A research on stereo matching algorithm for underwater image[C]//2014 4th International Congress on Image and Signal Processing,2011:850-854.
[14]Li Y Q,Zhang Y S,Li H B,et al.Underwater dense stereo matching based on depth constraint[J].Acta Photonica Sinica,2017,46(7):0715001.李雅倩,张岩松,李海滨,等.基于深度约束的水下稠密立体匹配[J].光子学报,2017,46(7):0715001.
[2]Zhang Q,Hao K,Li H B.Research on scale invariant feature transform feature matching based on underwater curve constraint[J].Acta Optica Sinica,2014,34(2):0215003.张强,郝凯,李海滨.水下环境中基于曲线约束的SIFT特征匹配算法研究[J].光学学报,2014,34(2):0215003.
[3]Zhang Q,Lu S Q,Li H B,et al.Research on underwater stereo matching method based on color segmentation[J].Acta Optica Sinica,2016,36(8):0815001.张强,卢士强,李海滨,等.基于色彩分割的水下立体匹配算法的研究[J].光学学报,2016,36(8):0815001.
[4]赵鹏.机器视觉研究与发展[M].北京:科学出版社,2012.
[5]Sanchez-Ferreira C,Mori J Y,Llanos C H,et al.Development of a stereo vision measurement architecture for an underwater robot[C]//2013 IEEE 4th Latin American Symposium on Circuits and Systems,2013:1-4.
[6]Lowe D G.Distinctive image features from scale-invariant keypoints[J].International Journal of Computer Vision,2004,60(2):91-110.
[7]Lowe D G.Object recognition from local scale-invariant features[C]//Proceedings of the Seventh IEEE International Conference on Computer Vision,1999,2:1150-1157.
[8]Rublee E,Rabaud V,Konolige K,et al.ORB:An efficient alternative to SIFT or SURF[C]//2011 IEEE International Conference on Computer Vision,2011:2564-2571.
[9]Peng H,Wen Y X,Zhai R F,et al.Stereo matching for binocular citrus images using SURF operator and epipolar constraint[J].Computer Engineering and Applications,2011,47(8):157-160.彭辉,文友先,翟瑞芳,等.结合SURF算子和极线约束的柑橘立体图像对匹配[J].计算机工程与应用,2011,47(8):157-160.
[10]Gedge J,Gong M L,Yang Y H.Refractive epipolar geometry for underwater stereo matching[C]//2011 Canadian Conference on Computer and Robot Vision,2011:146-152.
[11]Li J,Pan T S,Tseng K K,et al.Design of a monocular simultaneous localisation and mapping system with ORB feature[C]//2013 IEEE International Conference on Multimedia and Expo,2013:1-4.
[12]Zhang W M,Deng X X,Zhang Q,et al.Non-parallel system underwater image transformation model[J].Acta Photonica Sinica,2015,44(2):211002.张文明,邓茜雪,张强,等.基于非平行系统的水下图像转化模型[J].光子学报,2015,44(2):211002.
[13]Wang H B,Sun H Y,Shen J,et al.A research on stereo matching algorithm for underwater image[C]//2014 4th International Congress on Image and Signal Processing,2011:850-854.
[14]Li Y Q,Zhang Y S,Li H B,et al.Underwater dense stereo matching based on depth constraint[J].Acta Photonica Sinica,2017,46(7):0715001.李雅倩,张岩松,李海滨,等.基于深度约束的水下稠密立体匹配[J].光子学报,2017,46(7):0715001.