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Artificial Intelligence Techniques for the Recognition of Multi-Plate Multi-vehicle Tracking Systems: A Systematic Review

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Abstract

In recent years, the number of vehicles has been rising enormously, which has caused difficulties in detecting a vehicle and the person involved in any criminal activity or traffic violation. With the advent of Artificial Intelligence, the Automatic License Plate Recognition System has been used for quite some time. automatic licence plate recognition (ALPR) is a photosensitive identification system that identifies the license numbers after effective detection from an acquired image dataset. The ALPR system also plays a significant role in law enforcement and rendering services in smart cities. It is an automated system that can identify a vehicle by recognizing the characters of the license plate. This system is fundamental to traffic control and managing criminal activities, intelligent parking systems, and various applications. Also, it provides a brief outline of various license plate detection and recognition techniques reported by researchers in India and other countries. The comparative analysis also highlights the work done in the direction of automatic license plate recognition by the different researchers using various learning techniques and results obtained by using the detection rate, accuracy, and localization. This study follows an investigational approach to analyze the character recognition techniques used in ALPR systems; research challenges the researchers face. This paper contributes an extensive review of the existing scenario of ALPR systems.

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References

  1. Abedin MZ, Nath AC, Dhar P, Deb K, Hossain MS (2017) License plate recognition system based on contour properties and deep learning model. In: 2017 IEEE Region 10 humanitarian technology conference (R10-HTC), pp 590–593

  2. Kaur S (2016) An automatic number plate recognition system under image processing. Int J Intell Syst Appl 8(3):14–25

    Article  Google Scholar 

  3. Roberts DJ, Casanova M (2012)Automated License Plate Recognition (ALPR) Use by Law Enforcement: Policy and Operational Guide, Summary. https://www.ncjrs.gov/pdffiles1/nij/grants/239605.pdf

  4. Polishetty R, Roopaei M, Rad P (2016) A next-generation secure cloud-based deep learning license plate recognition for smart cities. In: 2016 15th IEEE international conference on machine learning and applications (ICMLA), pp 286–294

  5. Indira K, Mohan KV, Nikhilashwary T (2018) Automatic license plate recognition. Recent trends in signal and image processing advances in intelligent systems and computing. pp 67–77

  6. Ahmed AM, Aly SF (2019) Egyptian license plates recognition system using morphological operations and multi layered perceptron. In: The 9th conference on ICT in our lives

  7. Goncalves GR, Diniz MA, Laroca R, Menotti D, Schwartz WR (2018) Real-time automatic license plate recognition through deep multi-task networks. In: 2018 31st SIBGRAPI conference on graphics, patterns and images (SIBGRAPI), pp 110–117

  8. Barreto SC, Lambert JA, Vidal FDB (2019) Using synthetic images for deep learning recognition process on automatic license plate recognition. Lecture notes in computer science pattern recognition. Springer, Cham, pp 115–126

  9. Sanchez LF (2018) Automatic number plate recognition system using machine learning techniques. Unpublished Master’s Thesis, Cranfield University. https://addi.ehu.es/bitstream/handle/10810/29790/TFM_Leticia%20Fernandez.pdf?sequence=3&isAllowed=y

  10. Kakani BV, Gandhi D, Jani S (2017) Improved OCR based automatic vehicle number plate recognition using features trained neural network. In: 2017 8th international conference on computing, communication and networking technologies (ICCCNT)

  11. Negassi IT, Araya GG, Awawdeh M, Faisal T (2018) Smart car plate recognition system. In: 2018 1st international conference on advanced research in engineering sciences (ARES).

  12. Sferle RM, Moisi EV (2019) Automatic number plate recognition for a smart service auto. In: 2019 15th international conference on engineering of modern electric systems (EMES), pp 57–60

  13. Usmankhujaev S, Lee S, Kwon J (2019) Korean license plate recognition system using combined neural networks. In: 16th international conference advances in intelligent systems and computing, Distributed computing and artificial intelligence, pp 10–17

  14. Nazri MSBM, Gaafar TLAFBTL, Sofian H, Sajak, AAB (2020) IoT parking apps with car plate recognition for smart city using node red. In: 2020 11th international conference on information and communication systems (ICICS), pp 324–330

  15. Lin NH, Aung YL, Khaing WK (2018) Automatic vehicle license plate recognition system for smart transportation. In: 2018 IEEE international conference on internet of things and intelligence system (IOTAIS), pp 97–103

  16. Greati VR, Ribeiro VCT, Silva IMDD, Martins ADM (2017) A Brazilian license plate recognition method for applications in smart cities. In: 2017 IEEE first summer school on smart cities (S3C), pp 43–48

  17. Liou S-H, Hsieh Y-C, Chang C-Y (2018) Design and implementation of a smart parking management system for smart cities. In: 2018 IEEE international conference on consumer electronics-Taiwan (ICCE-TW)

  18. Pustokhina IV, Pustokhin DA, Rodrigues JJ, Gupta D, Khanna A, Shankar K, Seo C, Joshi GP (2020) Automatic vehicle license plate recognition using optimal K-means with convolutional neural network for intelligent transportation systems. IEEE Access 8:92907–92917

    Article  Google Scholar 

  19. Teixeira MA, Meneguette RI (2019) A real-time automatic plate recognition system based on optical character recognition and wireless Sensor Networks for ITS. Sensors 20(1):55

    Article  Google Scholar 

  20. Ravirathinam P, Patawari A (2019) Automatic license plate recognition for indian roads using faster-RCNN. In: 2019 11th international conference on advanced computing (ICoAC)

  21. Desai GG, Bartakke PP (2018) Real-time implementation of Indian license plate recognition system. In: 2018 IEEE Punecon

  22. Dias C, Jagetiya A, Chaurasia S (2019) Anonymous vehicle detection for secure campuses: a framework for license plate recognition using deep learning. In: 2019 2nd international conference on intelligent communication and computational techniques (ICCT), pp 79–82

  23. Babu RN, Sowmya V, Soman KP (2019) Indian car number plate recognition using deep learning. In: 2019 2nd international conference on intelligent computing, instrumentation and control technologies (ICICICT), pp 1269–1272

  24. Prabhu BS, Kalambur S, Sitaram D (2017) Recognition of Indian license plate number from live stream videos. In: 2017 International conference on advances in computing, communications and informatics (ICACCI), pp 2359–2365

  25. Puranic A, Deepak K, Umadevi V (2016) Vehicle number plate recognition system: a literature review and implementation using template matching. Int J Comput Appl 134(1):12–16

  26. Singh J, Bhushan B (2019) Real time Indian license plate detection using deep neural networks and optical character recognition using lstm tesseract. In: 2019 international conference on computing, communication, and intelligent systems (ICCCIS), pp 347–352

  27. Karwal H, Girdhar A (2015) Vehicle number plate detection system for Indian vehicles. In: 2015 IEEE international conference on computational intelligence and communication technology, pp 8–12

  28. Rabbani G, Islam MA, Azim MA, Islam MK, Rahman MM (2018) Bangladeshi license plate detection and recognition with morphological operation and convolution neural network. In: 2018 21st international conference of computer and information technology (ICCIT)

  29. Rokonuzzaman M, Amin MAA, Ahmed MHKMU, Rahman MT (2017) Automatic vehicle identification system using machine learning and robot operating system (ROS). In: 2017 4th international conference on advances in electrical engineering (ICAEE), pp 253–258

  30. Saif N, Ahmmed N, Pasha S, Shahrin MSK, Hasan MM, Islam S, Jameel ASMM (2019) Automatic license plate recognition system for Bangla license plates using convolutional neural network. In: TENCON 2019—2019 IEEE region 10 conference (TENCON), pp 925–930

  31. Jagtap J, Holambe S (2018) Multi-style license plate recognition using artificial neural network for Indian vehicles. In: 2018 International conference on information, communication, engineering and technology (ICICET), pp 1–4

  32. Kurdi MM, Elzein IA, Issa J, Ahmad IS (2017) Lebanese automated number plate reading based on neural network recognition. In: 2017 13th International computer engineering conference (ICENCO), pp 79–84

  33. Kusumadewi I, Sari CA, Setiadi DRIM, Rachmawanto EH (2019) License number plate recognition using template matching and bounding box method. J Phys Conf Ser 1201(012067):1–9

    Google Scholar 

  34. Haider SA, Khurshid K (2017) An implementable system for detection and recognition of license plates in Pakistan. In: 2017 international conference on innovations in electrical engineering and computational technologies (ICIEECT)

  35. Soomro SR, Javed MA, Memon, FA (2012) Vehicle number recognition system for automatic toll tax collection. In: 2012 international conference of robotics and artificial intelligence, pp 125–129

  36. Li T, Yu S (2015) Parallel license plate recognition scheme based on image splicing for intelligent transportation system. In: 2015 4th international conference on computer science and network technology (ICCSNT), pp 1482–1485

  37. Liu J, Li X, Zhang H, Liu C, Dou L, Ju L (2017) An implementation of number plate recognition without segmentation using convolutional neural network. In: 2017 IEEE 19th international conference on high performance computing and communications; IEEE 15th international conference on smart city; IEEE 3rd international conference on data science and systems (HPCC/SmartCity/DSS), pp 246–253

  38. He M-X, Hao P (2020) Robust automatic recognition of Chinese license plates in natural scenes. IEEE Access 8:173804–173814

    Article  Google Scholar 

  39. Ramazankhani F, Yazdian-Dehkordi M (2019) Iranian license plate detection using cascade classifier. In: 2019 27th Iranian conference on electrical engineering (ICEE), pp 1860–1863

  40. Rashtehroudi AR, Shahbahrami A, Akoushideh A (2020) Iranian license plate recognition using deep learning. In: 2020 international conference on machine vision and image processing (MVIP)

  41. Yogheedha K, Nasir A, Jaafar H, Mamduh S (2018) Automatic vehicle license plate recognition system based on image processing and template matching approach. In: 2018 international conference on computational approach in smart systems design and applications (ICASSDA).

  42. Keong WW, Iranmanesh V (2016) Malaysian automatic number plate recognition system using Pearson correlation. In: 2016 IEEE symposium on computer applications and industrial electronics (ISCAIE), pp 40–45

  43. Chai HY, Woon HH, Meng LK, Li YS (2014) Non-standard Malaysian car license plate recognition. In: 2014 IEEE symposium on computer applications and industrial electronics (ISCAIE), pp 152–157

  44. Htay MM, Gopalakrishnan AK (2016) Localization and recognition of a Myanmar license plate based on partially cut character structure. In: 2016 14th international conference on ICT and knowledge engineering (ICT&KE), pp 38–43

  45. Barnouti NH, Naser MAS, Al-Dabbagh SSM (2017) Automatic Iraqi license plate recognition system using back propagation neural network (BPNN). In: 2017 annual conference on new trends in information & communications technology applications (NTICT), pp 105–110

  46. Alaythawy AD (2020) Iraqi license plate recognition based on machine learning. Iraqi J Inf Commun Technol 3(4):1–10

    Article  Google Scholar 

  47. Alghyaline S (2020) Real-time Jordanian license plate recognition using deep learning. J King Saud Univ Comput Inf Sci. https://doi.org/10.1016/j.jksuci.2020.09.018

    Article  Google Scholar 

  48. Chaudhary MD, Chinchore JB (2014) Towards multiple license plate localization in Indian conditions: an edge density based approach. In: 2014 International conference on control, instrumentation, communication and computational technologies (ICCICCT), pp 60–65

  49. Kashyap A, Suresh B, Patil A, Sharma S, Jaiswal A (2018) Automatic number plate recognition. In: 2018 International conference on advances in computing, communication control and networking (ICACCCN), pp 838–843

  50. Zhou Y, Lv M, Ling Z, Li D (2019) Multiple license plate location algorithm in complex scene. In: 2019 IEEE international conferences on ubiquitous computing and communications (IUCC) and data science and computational intelligence (DSCI) and smart computing, networking and services (SmartCNS), pp 456–461

  51. Zubin Abraham V, Kurian B, Rajesh N (2011) Multiple license plate recognition for intelligent traffic management. In: 2011 annual IEEE India conference

  52. Guo J-M, Liu Y-F, Hsia C-H (2012) Multiple license plates recognition system. In: 2012 International conference on system science and engineering (ICSSE)

  53. Lin C-H, Wu C-H (2019) A lightweight, high-performance multi-angle license plate recognition model. In: 2019 international conference on advanced mechatronic systems (ICAMechS), pp 235–240

  54. Cao Y, Fu H, Ma H (2018) An end-to-end neural network for multi-line license plate recognition. In: 2018 24th international conference on pattern recognition (ICPR), pp 3698–3703

  55. Arora M, Jain A, Rustagi S, Yadav T (2019) Automatic number plate recognition system using optical character recognition. Int J Sci Res Comput Sci Eng Inf Technol. https://doi.org/10.32628/cseit1952280

  56. Ha PS, Shakeri M (2016) License plate automatic recognition based on edge detection. In: 2016 Artificial intelligence and robotics (IRANOPEN), pp 170–174

  57. Singh B, Kaur M, Singh D, Singh G (2016) Automatic number plate recognition system by character position method. Int J Comput Vis Robot 6(1/2):94–112

    Article  Google Scholar 

  58. Ismail M (2017) License plate recognition for moving vehicles case: at night and under rain condition. In: 2017 Second international conference on informatics and computing (ICIC)

  59. Jagadamba G, Purohit S, Chayashree G (2019) Campus vehicle monitoring through image processing. In: Power and Justice. Lecture notes in electrical engineering emerging research in electronics, computer science and technology. Springer, Singapore, pp 305–315

  60. Khan MA, Sharif M, Javed MY, Akram T, Yasmin M, Saba T (2018) License number plate recognition system using entropy-based features selection approach with SVM. IET Image Proc 12(2):200–209

    Article  Google Scholar 

  61. Felix AY, Jesudoss A, Mayan JA (2017) Entry and exit monitoring using license plate recognition. In: 2017 IEEE international conference on smart technologies and management for computing, communication, controls, energy and materials (ICSTM), pp 227–231

  62. Bjorklund T, Fiandrotti A, Annarumma M, Francini G, Magli E (2017) Automatic license plate recognition with convolutional neural networks trained on synthetic data. In: 2017 IEEE 19th international workshop on multimedia signal processing (MMSP).

  63. Do HN, Vo M-T, Vuong BQ, Pham HT, Nguyen AH, Luong HQ (2016) Automatic license plate recognition using mobile device. In: 2016 International conference on advanced technologies for communications (ATC), pp 268–271

  64. Lu Q, Liu Y, Huang J, Yuan X, Hu Q (2018) License plate detection and recognition using hierarchical feature layers from CNN. Multimedia Tools Appl 78(11):15665–15680

    Article  Google Scholar 

  65. Marzuki P, Syafeeza AR, Wong YC, Hamid NA, Alisa AN, Ibrahim MM (2019) A design of license plate recognition system using convolutional neural network. Int J Electr Comput Eng IJECE) 9(3):2196–2204

    Article  Google Scholar 

  66. Panahi R, Gholampour I (2017) Accurate detection and recognition of dirty vehicle plate numbers for high-speed applications. IEEE Trans Intell Transp Syst 18(4):767–779

    Article  Google Scholar 

  67. Saleem N, Muazzam H, Tahir HM, Farooq U (2016) Automatic license plate recognition using extracted features. In: 2016 4th international symposium on computational and business intelligence (ISCBI), pp 221–225

  68. Babbar S, Kesarwani S, Dewan N, Shangle K, Patel S (2018) A new approach for vehicle number plate detection. In: 2018 11th international conference on contemporary computing (IC3)

  69. Agarwal M, Krishnamurthi R (2020) Cognitive number plate recognition using machine learning and data visualization techniques. In: 2020 6th international conference on signal processing and communication (ICSC)

  70. Raza MA, Qi C, Asif MR, Khan MA (2020) An adaptive approach for multi-national vehicle license plate recognition using multi-level deep features and foreground polarity detection model. Appl Sci 10(6):2165

    Article  Google Scholar 

  71. Silva SM, Jung CR (2020) Real-time license plate detection and recognition using deep convolutional neural networks. J Vis Commun Image Represent 71:102773

    Article  Google Scholar 

  72. Henry C, Ahn SY, Lee S-W (2020) Multinational license plate recognition using generalized character sequence detection. IEEE Access 8:35185–35199

    Article  Google Scholar 

  73. Gupta S, Gupta MK, Kumar R (2021) A Novel Multi-Neural Ensemble Approach for Cancer Diagnosis. Appl Artif Intel 1–36

  74. Gupta S Gupta MK (2021) Computational model for prediction of malignant mesothelioma diagnosis. Comp J

  75. Gupta S, Gupta M (2021) Deep learning for brain tumor segmentation using magnetic resonance images. In: 2021 IEEE conference on computational intelligence in bioinformatics and computational biology (CIBCB), October 2021. IEEE, pp 1–6

  76. Gupta S, Gupta MK (2021) A comparative analysis of deep learning approaches for predicting breast cancer survivability. Arch Comput Methods Eng. https://doi.org/10.1007/s11831-021-09679-3

    Article  Google Scholar 

  77. Gupta S, Gupta MK (2021) Computational prediction of cervical cancer diagnosis using ensemble-based classification algorithm. Comput J. https://doi.org/10.1093/comjnl/bxaa198

    Article  Google Scholar 

  78. Kumar Y, Kaur K, Singh G (2020) Machine learning aspects and its applications towards different research areas. In: 2020 international conference on computation, automation and knowledge management (ICCAKM), Dubai, UAE, pp 150–156

  79. Kaur P, Kumar Y, Ahmed S, Alhumam A, Singla R et al (2022) Automatic license plate recognition system for vehicles using a CNN. CMC-Computers, Mater Contin 71(1):35–50

    Article  Google Scholar 

  80. Arora N, Kumar Y, Karkra R et al (2022) Automatic vehicle detection system in different environment conditions using fast R-CNN. Multimed Tools Appl. https://doi.org/10.1007/s11042-022-12347-8

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science & Engineering, Chandigarh Engineering College, Landran, Mohali, India

    Parneet Kaur

  2. Department of Computer Science & Engineering, Indus Institute of Technology & Engineering, Indus University, Ahmedabad, India

    Yogesh Kumar

  3. Model Institute of Engineering and Technology, Jammu, J&K, India

    Surbhi Gupta

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  1. Parneet Kaur
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Kaur, P., Kumar, Y. & Gupta, S. Artificial Intelligence Techniques for the Recognition of Multi-Plate Multi-vehicle Tracking Systems: A Systematic Review. Arch Computat Methods Eng 29, 4897–4914 (2022). https://doi.org/10.1007/s11831-022-09753-4

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