Research on License Plate Recognition Method Based on HALCON
Asian Journal of Research in Computer Science · pp. 1–11 · Published 19 Aug 2022
10.9734/ajrcos/2022/v14i330339Abstract
With the rapid development and continuous improvement of image processing technology, the intelligent management of traffic management system for vehicles has accelerated the speed of road safety information, in which the car license plate as the identification of vehicle identity, the identification of its character information is the key to the license plate recognition system. In order to solve the problem of the traditional license plate recognition algorithm such as long development period, this study adopts the HALCON as a programming platform, the acquisition of image preprocessing to enhance image contrast, through the affine transformation to complete correction of tilt of the image, and at the completion of the design after character segmentation OCR based on neural network classifier to complete accurate recognition of Chinese characters, letters and Numbers. The experiment shows that the system has the ability to adapt to the environment and can recognize the license plate information efficiently and accurately.
References (19)
- 1 Automated License Plate Recognition for Resource-Constrained Environments [DOI]
- 2 Robust Korean License Plate Recognition Based on Deep Neural Networks [DOI]
- 3 An improved visual SLAM based on affine transformation for ORB feature extraction [DOI]
- 4 Automatic Vehicle License Plate Recognition Using Optimal Deep Learning Model [DOI]
- 5 Traffic parameter estimation and control system based on machine vision [DOI]
- 6 Survey of Image Processing Based Applications in AMR [DOI]
- 7 A Simple Image Encryption Based on Binary Image Affine Transformation and Zigzag Process [DOI]
- 8 Research on Chinese License Plate Recognition Algorithm Based on Convolution Neural Network [DOI]
- 9 Recognition of Blurring Alphabet Character on Timing Pulley Drawing Based on Halcon Image Processing Technology [DOI]
- 10 Novel Method for Energy Consumption Billing Using Optical Character Recognition [DOI]
- 11 Deep learning-based isolated handwritten Sindhi character recognition [DOI]
- 12 Research on Pre-Processing Methods for License Plate Recognition [DOI]
- 13 A Study on the Advancement of Character Recognition Using Image Correction [DOI]
- 14 Optical Character Recognition using Deep Neural Network [DOI]
- 15 Research on VisualInspection System of Waterproof Breathable Membrane Based on HALCON [DOI]
- 16 License Plate recognition in fog weather based on deep learning [DOI]
- 17 A Dual-Watermarking Scheme Robust to Affine Transformation [DOI]
- 18 Improving the Transferability of Adversarial Examples with Image Affine Transformation [DOI]
- 19 ARPN Journal of Engineering and Applied Sciences [DOI]
Cited by 5
Kuisheng Wang, Chengwen Fu · 2023 8th International Conference on Intelligent Computing and Signal Processing (ICSP) · 2023
Longwen Wu, Yi Gan · Microchemical Journal · 2025
Chunping Liu, Longgong Xu, Di Miao · IEEE Access · 2025
Showing 3 of 5 known citations — external sources report more than can currently be individually listed.
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