Urban Cable Field Inspection Technology Based on MR Technology

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2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 103))

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Abstract

By introducing the real scene information of cable inspection into the simulation scene, hybrid reality technology (MR) brings wonderful experience to the inspection operator, and establishes the information exchange between the inspection operator and the real scene and virtual scene, which is the further development of cable intelligent inspection technology. This paper first describes the advantages and characteristics of hybrid reality technology and the development status at home and abroad, and then designs a virtual scene image segmentation algorithm of hybrid reality technology for cable inspection. The purpose is to obtain better visual effect of cable inspection scene, and realize the effective construction of virtual environment for cable inspection, the recovery of real environment space structure, and the realization of image segmentation And the natural integration of virtual and real environment. Finally, the MR effect of cable field inspection is given. The practical application shows that the technology can help the field staff to realize manual inspection more intelligently and efficiently, and make the field operation more standardized.

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References

  1. Eunji P (2013) A study on the application of QR code through case study focused on logistics and distribution sector. J Korea Port Econ Assoc 29(4):247–264

    Google Scholar 

  2. Dutta K, Bhattacharjee D, Nasipuri M et al (2021) Complement component face space for 3D face recognition from range images. Appl Intell 51(10):1–18

    Google Scholar 

  3. Sadhya D, Singh SK (2019) A comprehensive survey of unimodal facial databases in 2D and 3D domains. Neurocomputing 358(17):188–210

    Article  Google Scholar 

  4. Al-Salihi SK, Aydin S, Ghaeb NH (2021) SWFT: subbands wavelet for local features transform descriptor for corneal diseases diagnosis. Turk J Electr Eng Comput Sci 29(2):875–896

    Article  Google Scholar 

  5. Kornilov K, Soldatova S, Povetkin P (2021) Study of local features of antihypertensive drugs pharmacoepidemiology as a means of hypotensive therapy optimization ways searching. Therapy 2(2021):29–38

    Article  Google Scholar 

  6. Altameemi A, Abbas HH (2019) Biological landmark versus quasi-landmarks for 3D face recognition and gender classification. Int J Electr Comput Eng 9(5):295–311

    Google Scholar 

  7. Nassih B, Amine A, Ngadi M et al (2021) An efficient three-dimensional face recognition system based random forest and geodesic curves. Comput Geom 132(11):226–234

    MathSciNet  MATH  Google Scholar 

  8. Skrzypecki J, Patel MS, Suh LH (2019) Performance of the Barrett Toric calculator with and without measurements of posterior corneal curvature. Eye 33(11):73–88

    Article  Google Scholar 

  9. Vivian NI, Ise OA (2020) Face Recognition service model for student identity verification using deep neural network and support vector machine (SVM). Int J Sci Res Comput Sci Eng Inf Technol 6(4):11–20

    Google Scholar 

  10. Jothi JN, Letitia S (2020) Tampering detection using hybrid local and global features in wavelet-transformed space with digital images. Soft Comput 24(7):5427–5443

    Article  Google Scholar 

Download references

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Correspondence to Yan Xu .

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Xu, Y., Shan, L., Meng, Q., Peng, H., Huang, Y. (2022). Urban Cable Field Inspection Technology Based on MR Technology. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) 2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City. Lecture Notes on Data Engineering and Communications Technologies, vol 103. Springer, Singapore. https://doi.org/10.1007/978-981-16-7469-3_117

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