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Research on Object Detection and Shadow Detection Algorithm Based on Computer Vision

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

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 102))

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Abstract

Nowadays, many substances, whether appearance or internal structure, are recorded in the form of data. The appearance of substances observed by human eyes will vary according to people’s visual perception. Research found that the application of computer vision can objectively and effectively record a variety of materials and things related data. Computer vision is an interdisciplinary field that studies how to make computer acquire advanced understanding from digital image or video. Its main purpose is to complete various complex tasks automatically instead of human eye, such as acquiring information, processing information, analyzing and understanding digital image, etc., and to provide information for decision-making according to the analysis and processing of relevant data.

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References

  1. Song Q (2017) Research on object detection and shadow detection algorithm based on computer vision. Jilin University, Changchun

    Google Scholar 

  2. Huang X (2016) Improvement of target detection and tracking algorithm based on computer vision. Qingdao University, Qingdao

    Google Scholar 

  3. Zeng W (2016) Research on foreground object detection algorithm in computer vision. Shandong University, Jinan

    Google Scholar 

  4. Wang Z (2015) Robustness evaluation of shadow features and shadow detection algorithm. Shenyang University of Technology, Shenyang

    Google Scholar 

  5. Guo X (2018) Research on object detection and shadow detection algorithm based on computer vision. J Jiangxi Electr Power Vocat Techn Coll (03)

    Google Scholar 

  6. Dong Y, Feng H, Xu Z, Chen Y, Li Q (2019) Attention res UNET: an efficient shadow detection algorithm. J Zhejiang Univ (Eng Ed) (02)

    Google Scholar 

  7. Sun D, Zhao M (2016) Analysis of shadow detection method in parking video surveillance system. Eng Technol Res (06)

    Google Scholar 

  8. Chen Z, Liu Y, Yang H (2019) High order energy equation shadow detection algorithm for single outdoor image. Chin J Comput Aided Des Graph (07)

    Google Scholar 

  9. Liao J, Liu L (2017) Shadow detection method based on color image shadow attribute analysis. J Nat Sci Xiangtan Univ (04)

    Google Scholar 

  10. Liao J, Zhu D, Li B, Liu L, Chen Q (2017) Moving shadow detection based on color ratio and gradient invariance. Comput Eng Appl (22)

    Google Scholar 

  11. Tang G, Xie Y, Zhu X (2021) Application of ship shadow detection algorithm in video image. Ship Sci Technol (06)

    Google Scholar 

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Correspondence to Qingxing Liu .

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Liu, Q., Zhou, C. (2022). Research on Object Detection and Shadow Detection Algorithm Based on Computer Vision. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) 2021 International Conference on Big Data Analytics for Cyber-Physical System in Smart City. BDCPS 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 102. Springer, Singapore. https://doi.org/10.1007/978-981-16-7466-2_146

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