Accuracy Improvement of a Province Name Recognition on Thai License Plate

Kraisin, Somkheart; Kaothanthong, Natsuda

doi:10.1109/isai-nlp.2018.8692983

Cited by 6 publications

(8 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the Google Cloud Vision API may be less customizable owing to the availability of in-built services. When comparing the accuracy of the technique with other articles on Thai language recognition as detailed in Table 3, this paper found that the articles [33], [41]- [43] used the actual cases as a sample and there has higher accuracy than the proposed method. However, when studying the details of each article, article [41] recognized only six-digit numbers of the Thai lottery ticket.…”

Section: Discussion and Suggestionmentioning

confidence: 99%

See 1 more Smart Citation

Comparative analysis of Tesseract and Google Cloud Vision for Thai vehicle registration certificate

Thammarak

Kongkla

Sirisathitkul

et al. 2022

IJECE

View full text Add to dashboard Cite

Optical character recognition (OCR) is a technology to digitize a paper-based document to digital form. This research studies the extraction of the characters from a Thai vehicle registration certificate via a Google Cloud Vision API and a Tesseract OCR. The recognition performance of both OCR APIs is also examined. The 84 color image files comprised three image sizes/resolutions and five image characteristics. For suitable image type comparison, the greyscale and binary image are converted from color images. Furthermore, the three pre-processing techniques, sharpening, contrast adjustment, and brightness adjustment, are also applied to enhance the quality of image before applying the two OCR APIs. The recognition performance was evaluated in terms of accuracy and readability. The results showed that the Google Cloud Vision API works well for the Thai vehicle registration certificate with an accuracy of 84.43%, whereas the Tesseract OCR showed an accuracy of 47.02%. The highest accuracy came from the color image with 1024×768 px, 300dpi, and using sharpening and brightness adjustment as pre-processing techniques. In terms of readability, the Google Cloud Vision API has more readability than the Tesseract. The proposed conditions facilitate the possibility of the implementation for Thai vehicle registration certificate recognition system.

show abstract

Section: Discussion and Suggestionmentioning

confidence: 99%

“…However, when studying the details of each article, article [41] recognized only six-digit numbers of the Thai lottery ticket. Articles [33], [42], [43] recognized the Thai sign and the car license plate. It contains characters and lines less complexity than the Thai vehicle registration certificate.…”

Section: Discussion and Suggestionmentioning

confidence: 99%

Comparative analysis of Tesseract and Google Cloud Vision for Thai vehicle registration certificate

Thammarak

Kongkla

Sirisathitkul

et al. 2022

IJECE

View full text Add to dashboard Cite

show abstract

“…The license plate for recognition has been sequentially identified by CNN classifier. As 64 vehicles entered this region illegally, data was composed manually from the science pictures, and 59 IDs were accurately detected using this tool [2]. Introduction The identification of license plates is a very good source of knowledge for record detection and recognition.…”

Section: Literature Reviewmentioning

confidence: 99%

Effective Plate Object Segmentation and Recognition by Implementing Artificial Intelligent Model for Smart Transportation Systems.

Mr. Mehul T. Patel, Dr. Ashishkumar Parejiya

2023

tjjpt

View full text Add to dashboard Cite

The increase in the number of vehicles in the last few years has made it challenging to manually note the number plate text of the vehicle. Hence, in order to reduce the manual work, there is a need to propose a methodology that can detect the number plate region from the input image and recognize the characters of the number plate. Systems have been built for the same using Image Processing techniques, but this technique fails to provide accurate results occasionally in the case of real data. Modern technology such as Deep Learning overcomes this problem. Hence, a deep learning-based methodology is proposed to detect the number plate region from the input image and recognize its characters. Using the pre-trained based deep learning Networks. the number plate region is detected and using Convolutional Neural Networks (CNN), the characters are recognized from the detected plate region. The system also stores the number plate text with its state name into the database to maintain a record of number plates detected. The proposed system provides promising results. The model is judged against other models that are already out there, such as ResNet50, DenseNet, and DenseCapsNet. According to these studies, MobileNet has reached a level of accuracy of 98.69%, which is higher than other algorithms that are thought to be cutting-edge.

show abstract

“…Furthermore, Chomphuwiset [16] presented a technique for recognising printed Thai characters using a feature-based technique and a convolutional neural network (CNN). Other related studies have also found techniques to improve the accuracy of Thai character recognition such as using string matching [35], histogram of gradients (HOG) [36,37], color layout descriptors [36], normalised correlation coefficients [36], and circular-scan histograms [38]. Regarding the level of accuracy, available techniques for Thai character recognition from images have an accuracy rate of 75-98%; Chomphuwiset [16] applied his method to actual cases, achieving an accuracy of 98.00%.…”

Section: Figure 2 Example Of a Thai Word With Three Elements: Letters...mentioning

confidence: 99%

“…Jirattitichareon & Chalidabhongse [40] used a Gaussian mixture model for the detection and segmentation of text in low-quality Thai sign images. In addition, Kraisin & Kaothanthong [37] applied the HOG feature descriptor to improve the accuracy of provincial name recognition on a Thai license plate. Alternatively, post-processing involves data-cleaning steps for digitised documents.…”

Section: Figure 2 Example Of a Thai Word With Three Elements: Letters...mentioning

confidence: 99%

Automated Data Digitization System for Vehicle Registration Certificates Using Google Cloud Vision API

Thammarak

Sirisathitkul²,

Kongkla³

et al. 2022

Civ Eng J

View full text Add to dashboard Cite

This study aims to develop an automated data digitization system for the Thai vehicle registration certificate. It is the first system developed as a web service Application Programming Interface (API), which is essential for any enterprise to increase its business value. Currently, this system is available on “www.carjaidee.com”. The system involves four steps: 1) an embedded frame aligns a document to be correctly recognised in the image acquisition step; 2) sharpening and brightness filtering techniques to enhance image quality are applied in the pre-processing step; 3) the Google Cloud Vision API receives a prompt to proceed in the recognition step; 4) a specific domain dictionary to improve accuracy rate is developed for the post-processing step. This study defines 92 images for the experiment by counting the correct words and terms from the output. The findings suggest that the proposed method, which had an average accuracy of 93.28%, was significantly more accurate than the original method using only the Google Cloud Vision API. However, the system is limited because the dictionaries cannot automatically recognise a new word. In the future, we will explore solutions to this problem using natural language processing techniques. Doi: 10.28991/CEJ-2022-08-07-09 Full Text: PDF

show abstract

Accuracy Improvement of a Province Name Recognition on Thai License Plate

Cited by 6 publications

References 15 publications

Comparative analysis of Tesseract and Google Cloud Vision for Thai vehicle registration certificate

Comparative analysis of Tesseract and Google Cloud Vision for Thai vehicle registration certificate

Effective Plate Object Segmentation and Recognition by Implementing Artificial Intelligent Model for Smart Transportation Systems.

Automated Data Digitization System for Vehicle Registration Certificates Using Google Cloud Vision API

Contact Info

Product

Resources

About