Robust image matching constrained by delaunay triangulation

doi:10.11947/j.AGCS.2020.20190089

Abstract

Abstract: Image matching is an important issue in the fields of photogrammetry and computer vision. This study exploits the usage of Delaunay triangulation for reliable image matching. First, randomly located initial matches are organized by using Delaunay triangulation, and neighboring connection relationships are established evenly and stably. Second, local photometric and geometric constraints are constructed based on the line descriptor and spatial angular order, which converts the problem of removing outliers to that of analyzing the similarity of the Delaunay triangulation and its corresponding graph. Third, a match expansion operation is implemented based on the local geometric constraint deduced from two corresponding triangles. Finally, a reliable image matching method is proposed with the assistant of the hierarchical elimination and cross-checking strategies. The proposed algorithm is verified by using three datasets, and the results demonstrate that even with high outlier ratios the proposed method can reliably remove false matches and provide match results with high precision.

Key words: digital photogrammetry, image matching, Delaunay triangulation, line descriptor

CLC Number:

P231
P208

JIANG San, JIANG Wanshou. Robust image matching constrained by delaunay triangulation[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(3): 322-333.

References

[1] TSAI C H, LIN Y C. An accelerated image matching technique for UAV orthoimage registration[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2017, 128:130-145.
[2] JIANG San, JIANG Wanshou. Efficient structure from motion for oblique UAV images based on maximal spanning tree expansion[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2017, 132:140-161.
[3] 闫利, 费亮, 叶志云, 等. 大范围倾斜多视影像连接点自动提取的区域网平差法[J]. 测绘学报, 2016, 45(3):310-317, 338. DOI:10.11947/j.AGCS.2016.20140673. YAN Li, FEI Liang, YE Zhiyun, et al. Automatic tie-points extraction for triangulation of large-scale oblique multi-view images[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(3):310-317, 338. DOI:10.11947/j.AGCS.2016.20140673.
[4] 薛武, 张永生, 赵玲, 等. 增量式SFM与POS辅助光束法平差精度比较[J]. 测绘学报, 2017, 46(2):198-207. DOI:10.11947/j.AGCS.2017.20160274. XUE Wu, ZHANG Yongsheng, ZHAO Ling, et al. Compareison of the accuracy of incremental SFM with POS-aided bundle adjustment[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(2):198-207. DOI:10.11947/j.AGCS.2017.20160274.
[5] MUSIALSKI P, WONKA P, ALIAGA D G, et al. A survey of urban reconstruction[J]. Computer Graphics Forum, 2013, 32(6):146-177.
[6] HARRIS C, STEPHENS M. A combined corner and edge detector[C]//Proceedings of the 4th Alvey Vision Conference. Manchester:[s.n.], 1988.
[7] ACKERMANN F. Digital image correlation:performance and potential application in photogrammetry[J]. The Photogrammetric Record, 1984, 11(64):429-439.
[8] FISCHLER M A, BOLLES R C. Random sample consensus:a paradigm for model fitting with applications to image analysis and automated cartography[J]. Communications of the ACM, 1981, 24(6):381-395.
[9] CHUM O, MATAS J, KITTLER J. Locally optimized RANSAC[C]//Proceedings of the 25th DAGM Symposium on Pattern Recognition. Berlin:Springer, 2003:236-243.
[10] CHUM O, MATAS J. Matching with PROSAC-progressive sample consensus[C]//Proceedings of 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego:IEEE, 2005:220-226.
[11] RAGURAM R, CHUM O, POLLEFEYS M, et al. USAC:a universal framework for random sample consensus[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(8):2022-2038.
[12] LI Xinchao, LARSON M, HANJALIC A. Pairwise geometric matching for large-scale object retrieval[C]//Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition. Boston:IEEE, 2015:5153-5161.
[13] LU Luping, ZHANG Yong, TAO Pengjie. Geometrical consistency voting strategy for outlier detection in image matching[J]. Photogrammetric Engineering & Remote Sensing, 2016, 82(7):559-570.
[14] SATTLER T, LEIBE B, KOBBELT L. SCRAMSAC:improving RANSAC's efficiency with a spatial consistency filter[C]//Proceedings of 2009 IEEE 12th International Conference on Computer Vision. Kyoto:IEEE, 2009:2090-2097.
[15] HU Han, ZHU Qing, DU Zhiqiang, et al. Reliable spatial relationship constrained feature point matching of oblique aerial images[J]. Photogrammetric Engineering & Remote Sensing, 2015, 81(1):49-58.
[16] LIU Zhe, MARLET R. Virtual line descriptor and semi-local matching matching method for reliable feature correspondence[C]//British Machine Vision Conference. United Kingdom:[s.n.], 2012:16.1-16.11.
[17] LI Jiayuan, HU Qingwu, AI Mingyao. 4FP-structure:a robust local region feature descriptor[J]. Photogrammetric Engineering & Remote Sensing, 2017, 83(12):813-826.
[18] LOWE D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 2004, 60(2):91-110.
[19] LI Yan, TSIN Y, GENC Y, et al. Object detection using 2D spatial ordering constraints[C]//Proceedings of 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego:IEEE, 2005:711-718.
[20] LIU Zhaoxia, AN Jubai, JING Yu. A simple and robust feature point matching algorithm based on restricted spatial order constraints for aerial image registration[J]. IEEE Transactions on Geoscience and Remote Sensing, 2012, 50(2):514-527.
[21] MIKOLAJCZYK K, SCHMID C. A performance evaluation of local descriptors[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(10):1615-1630.
[22] MOISAN L, STIVAL B. A probabilistic criterion to detect rigid point matches between two images and estimate the fundamental matrix[J]. International Journal of Computer Vision, 2004, 57(3):201-218.
[23] MA Jiayi, ZHAO Ji, TIAN Jinwen, et al. Robust point matching via vector field consensus[J]. IEEE Transactions on Image Processing, 2014, 23(4):1706-1721.
[24] MA Jiayi, ZHOU Huabing, ZHAO Ji, et al. Robust feature matching for remote sensing image registration via locally linear transforming[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(12):6469-6481.
[25] IZADI M, SAEEDI P. Robust weighted graph transformation matching for rigid and nonrigid image registration[J]. IEEE Transactions on Image Processing, 2012, 21(10):4369-4382.