Abstract
The above chapters focus on the semi-physical verification technology in the field of RFID system. With the continuous development of technology, the semi-physical verification technology is not only widely used in the field of RFID system, but also promoted in other fields, such as internet of vehicles (IOV), navigation and structural health monitoring.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Mallik S (2014) Intelligent transportation system. Int J Civil Eng Res 5(4):367–372
Zhang W, Xi X (2016) The innovation and development of internet of vehicles. China Commun 13(5):122–127
Tang L (2013) Vehicle networking technology and application. Science Press, Beijing
Wang L, Tao S, Lin H et al (2015) Multi-mode electronic vehicle identification in the scene of multi-lane free flow. In: International conference on connected vehicles and expo (ICCVE), Shenzhen, China, Oct 2015, pp 360–361
Ministry of Industry and Information Technology of the People’s Republic of China (2011) Internet of things “Twelfth Five Year Plan” for development
Ministry of Transport of the People’s Republic of China (2014) Measures for the dynamic supervision and administration of road transport vehicles
Ministry of Industry and Information Technology of the People’s Republic of China (2015) Internet of things innovation plan of action (2015–2020)
Marais H, Grobler MJ, Holm JEW (2013) Modeling of an RFID-based electronic vehicle identification system. In: AFRICON conference, Pointe aux Piments, Mauritius, Sept 2013, pp 303–307
Colella R, Catarinucci L, Coppola P et al (2016) Measurement platform for electromagnetic characterization and performance evaluation of UHF RFID tags. IEEE Trans Instrum Meas 65(4):905–914
Hu H, Li B, Chen X et al (2016) Adaptability evaluation of electronic vehicle identification in urban traffic: a case study of Beijing. Tehički vjesnik 23(1):171–179
Maglaras LA, Al-Bayatti AH, He Y et al (2016) Social internet of vehicles for smart cities. J Sens Actuator Netw 5(1):3
Center China Article Coding (2003) Barcode technology and application. Tsinghua University Press, Beijing
Furness A (2000) Machine-readable data carriers—a brief introduction to automatic identification and data capture. Assembly Autom 20(1):28–34
Swartz J, Wang YP (1990) Fundamentals of barcode information theory. Computer 23(4):74–86
National Quality and Technical Supervision (2000) People’s Republic of China national standard barcode terminology. China Standard Press, Beijing
GB/T 23704-2009, Information technology. Automatic identification and data acquisition techniques. Verification of two dimensional barcode symbol printing quality
Chen C, Kot AC, Yang H (2013) A two-stage quality measure for mobile phone captured 2D barcode images. Pattern Recogn 46(9):2588–2598
Chen C, Kot AC, Yang H (2010) A quality measure of mobile phone captured 2D barcode images. In: IEEE international conference on image processing, Hong Kong, Sept 2010, pp 329–332
Yang H, Kot AC, Jiang X (2012) Binarization of low-quality barcode images captured by mobile phones using local window of adaptive location and size. IEEE Trans Image Process 21(1):418–425
Sheng HL (2011) High-speed barcode quality online detection technology. Huazhong University of Science and Technology, Wuhan
Xiu JH, Huang P, Li J et al (2012) Radiometric calibration of large area array color CCD aerial mapping camera. Guangxue Jingmi Gongcheng (Opt Precis Eng) 20(6):1365–1373
Chander G, Markham BL, Helder DL (2009) Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sens Environ 113(5):893–903
Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern 9(1):62–66
Chaki N, Shaikh SH, Saeed K (2014) A comprehensive survey on image binarization techniques. Springer India, New Delhi
Wu J, Yang Z, Han D et al (2010) 2D barcode image binarization based on wavelet and Otsu method. Comput Eng 10:067
Chu CH, Yang DN, Chen MS (2007) Image stabilization for 2D barcode in handheld devices. In: International conference on multimedia, Augsburg, Germany, Sept 2007, pp 697–706
Xu W, Mccloskey S (2011) 2D Barcode localization and motion deblurring using a flutter shutter camera. In: IEEE workshop on applications of computer vision, Washington, DC, Jan 2011, pp 159–165
Ha JE (2011) A new method for detecting data matrix under similarity transform for machine vision applications. Int J Control Autom Syst 9(4):737–741
Leong LK, Wang Y (2009) Extraction of 2D barcode using keypoint selection and line detection. In: Advances in multimedia information processing-PCM 2009, Springer, Berlin, pp 826–835
Belussi LFF, Hirata NST (2013) Fast component-based QR code detection in arbitrarily acquired images. J Math Imaging Vis 45(3):277–292
Joseph E, Pavlidis T (1991) Waveform recognition with application to barcodes. In: IEEE international conference on systems, man, and cybernetics, Anchorage, Alaska, Oct 1991, pp 129–134
Hu H, Xu W, Huang Q (2009) A 2D barcode extraction method based on texture direction analysis. In: International conference on image and graphics, Xi’an, China, Sept 2009, pp 759–762
Gonzalez RC, Woods RE, Masters BR (2010) Digital image processing, 3rd edn. Prentice Hall, New Jersey
Melkman AA (1987) On-line construction of the convex hull of a simple polyline. Inf Process Lett 25(1):11–12
Jung CR, Schramm R (2004) Rectangle detection based on a windowed Hough transform. In: 17th Brazilian symposium on computer graphics and image processing, Curitiba, Brazil, Oct 2004, pp 113–120
Qian K, Yu XL, Yu YS et al (2015) Design for two-dimensional barcode dynamic recognition system in the environment of large-scale logistics. In: IEEE advanced information technology, electronic and automation control conference, Chongqing, China, Dec 2015, vol 12, pp 878–882
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2019 Science Press, Beijing and Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Yu, X., Wang, D., Zhao, Z. (2019). Application of Semi-physical Verification Technology in Other Areas of IOT. In: Semi-physical Verification Technology for Dynamic Performance of Internet of Things System. Springer, Singapore. https://doi.org/10.1007/978-981-13-1759-0_7
Download citation
DOI: https://doi.org/10.1007/978-981-13-1759-0_7
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-1758-3
Online ISBN: 978-981-13-1759-0
eBook Packages: EngineeringEngineering (R0)