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The Geometric Transformation Model of Two Views Based on the Line-Scan Camera Imaging Model

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13458))

Abstract

With the increasing use of line-scan camera, it is difficult to ensure that its sensor is parallel to the target in imaging. This will make the target present a different appearance in linear array images. When two linear array images are registered, it is crucial to choose a suitable geometric transformation model. However, the imaging model of line-scan camera is different from that of frame camera, and the classical geometric transformation model of frame image, namely perspective transformation model, does not conform to geometric transformation of linear array image. Therefore, according to the imaging model of line-scan camera, the geometric transformation model of linear array image is derived in this paper. To obtain linear array images, an acquisition system is built. The geometric transformation model established in this paper and perspective transformation model are used to register the linear array images respectively. The registration results based on the geometric transformation model of linear array image show that the two linear array images can be completely aligned and the root mean square error of feature points is smaller. On the contrary, the registration results based on perspective transformation model show that the two images are not alignment, and the root mean square error of feature points is larger, which also indicates that it is not suitable for geometric transformation of linear array images.

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References

  1. Hui, B.W., et al.: Line-scan camera calibration in close-range photogrammetry. Opt. Eng. 51(5), 053602 (2012). https://doi.org/10.1117/1.OE.51.5.053602

    Article  Google Scholar 

  2. Ye, Y.X., et al.: Robust registration of multimodal remote sensing images based on structural similarity. IEEE Trans. Geosci. Remote Sens. 55(5), 2941–2958 (2017). https://doi.org/10.1109/TGRS.2017.2656380

    Article  Google Scholar 

  3. Iwasaki, A., Fujisada, H.: ASTER geometric performance. IEEE Trans. Geosci. Remote Sens. 43(12), 2700–2706 (2005). https://doi.org/10.1109/TGRS.2005.849055

    Article  Google Scholar 

  4. Liu, C.C.: Processing of FORMOSAT-2 daily revisit imagery for site surveillance. IEEE Trans. Geosci. Remote Sens. 44(11), 3206–3214 (2006). https://doi.org/10.1109/TGRS.2006.880625

    Article  Google Scholar 

  5. Storey, J.C., Choate, M.J., Meyer, D.J.: A geometric performance assessment of the EO-1 advanced land imager. IEEE Trans. Geosci. Remote Sens. 42(3), 602–607 (2004). https://doi.org/10.1109/TGRS.2003.820603

    Article  Google Scholar 

  6. Zhu, Z.S., et al.: High precision matching and 3D surface reconstruction of Chang’E 1 lunar images. Acta Opt. Sin. 34(2), 92–100 (2014)

    Google Scholar 

  7. Peng, W., et al.: A high performance real-time vision system for curved surface inspection. Optik 232, 166514 (2021). https://doi.org/10.1016/j.ijleo.2021.166514

    Article  Google Scholar 

  8. Usamentiaga, R., Garcia, D.F., de la Calle, F.J.: Line-scan camera calibration: a robust linear approach. Appl. Opt. 59(30), 9443 (2020). https://doi.org/10.1364/AO.404774

    Article  Google Scholar 

  9. Zhan, D., et al.: Study on high-speed and dynamic vision measurement approach for overhead catenary system geometric parameter inspection. Chin. J. Sci. Instrum. 35(8), 1852–1859 (2014)

    Google Scholar 

  10. Xu, J.Y., et al.: Correction of rolling wheel images captured by a linear array camera. Appl. Opt. 54, 9736–9740 (2015). https://doi.org/10.1364/AO.54.009736

    Article  Google Scholar 

  11. Liu, L., Zhou, F.Q., He, Y.Z.: Automated visual inspection system for bogie block key under complex freight train environment. IEEE Trans. Instrum. Meas. 65(1), 2–14 (2016). https://doi.org/10.1109/TIM.2015.2479101

    Article  Google Scholar 

  12. Lu, S.F., Liu, Z.: Automatic visual inspection of a missing split pin in the China railway high-speed. Appl. Opt. 55(30), 8395–8405 (2016). https://doi.org/10.1364/AO.55.008395

    Article  Google Scholar 

  13. Lu, S.F., Liu, Z., Shen, Y.: Automatic fault detection of multiple targets in railway maintenance based on time-scale normalization. IEEE Trans. Instrum. Meas. 67(4), 849–865 (2018). https://doi.org/10.1109/TIM.2018.2790498

    Article  Google Scholar 

  14. Gupta, R., Hartley, R.I.: Linear pushbroom camera. IEEE Trans. Pattern Anal. Mach. Intell. 19(9), 963–975 (1997). https://doi.org/10.1109/34.615446

    Article  Google Scholar 

  15. Bartoli, A.: Groupwise geometric and photometric direct image registration. IEEE Trans. Pattern Anal. Mach. Intell. 30(12), 2098–2108 (2008). https://doi.org/10.1109/TPAMI.2008.22

    Article  Google Scholar 

  16. Geiger, A., et al.: Automatic camera and range sensor calibration using a single shot. In: IEEE International Conference on Robotics and Automation, pp. 3936–3943 (2012). https://doi.org/10.1109/ICRA.2012.6224570

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Acknowledgement

This research was supposed by the Science and Technological Innovation Field Fund Projects (No. E01Z041101).

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Correspondence to Lei Fang .

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Fang, L., Shi, Z., Liu, Y., Li, C., Zhao, E. (2022). The Geometric Transformation Model of Two Views Based on the Line-Scan Camera Imaging Model. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13458. Springer, Cham. https://doi.org/10.1007/978-3-031-13841-6_11

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  • DOI: https://doi.org/10.1007/978-3-031-13841-6_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13840-9

  • Online ISBN: 978-3-031-13841-6

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