Comparative Analysis of EasyOCR and TesseractOCR for Automatic License Plate Recognition using Deep Learning Algorithm

Vedhaviyassh, D.R.; Sudhan, R.; Saranya, G.; Safa, M.; Arun, D

doi:10.1109/iceca55336.2022.10009215

Cited by 21 publications

(8 citation statements)

References 15 publications

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“…In research done by D.R.Vedhaviyassh, R.Sudhan, G.Saranya, M.Safa, and D. Arun that made comparisons using EasyOCR and TesseractOCR on License Plate Recognition using Deep Learning Algorithm, it was found the EasyOCR performed better at recognizing correct license plates 95% which is 5% better than TesseractOCR. This supports the claim of EasyOCR being used for smaller chunks of texts [6].…”

Section: Analysis Of License Plate Recognition Using Easyocr and Tess...supporting

confidence: 85%

Analysis of Optical Character Recognition using EasyOCR under Image Degradation

Salehudin,

Basah,

Yazid

et al. 2023

J. Phys.: Conf. Ser.

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This project explores EasyOCR’s performance with Latin characters under image degradation. Variables like character-background intensity difference, Gaussian blur, and relative character size were tested. EasyOCR excels in distinguishing unique lowercase and uppercase characters but tends to favor uppercase for similar shapes like C, S, U, or Z. Results showed that high character-background intensity differences affected OCR output, with confidence scores ranging from 3 % to 80%. Higher differences caused confusion between characters like o and 0, or i and 1. Increased Gaussian blur hindered recognition but improved it for certain letters like v. Image size had a significant impact, with character detection failing as sizes decreased to 40% to 30% of the original. These findings provide insights into EasyOCR’s capabilities and limitations with Latin characters under image degradation.

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Section: Analysis Of License Plate Recognition Using Easyocr and Tess...supporting

confidence: 85%

Analysis of Optical Character Recognition using EasyOCR under Image Degradation

Salehudin,

Basah,

Yazid

et al. 2023

J. Phys.: Conf. Ser.

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“…Additionally, helmet detection involves assessing overlapping bounding boxes and verifying helmet presence within specified coordinates, while number plate recognition utilizes EasyOCR. D.R.Vedhaviyassh [24] proposes a threemodule system for license plate recognition, utilizing OpenCV for image acquisition, YOLOv5 for plate detection, and OCR methods (Tesseract OCR and EasyOCR) for character recognition. The results demonstrate that EasyOCR achieves over 95% accuracy in predicting number plates, surpassing Tesseract OCR's 90%, highlighting its superior performance in real-time predictions through its deep learning approach for object recognition.…”

Section: Related Workmentioning

confidence: 99%

A comprehensive review on helmet detection and number plate recognition approaches

Vijendar Reddy,

Gandla,

Veldurthi

et al. 2024

E3S Web of Conf.

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Motorbikes serve as the primary mode of transportation in most countries as they are cost effective and appropriate for a nuclear family. But it has been observed that more than 70% of the users do not prefer to wear safety helmets for various reasons jeopardizing their lives and falling prey to accidents. The most prevalent method for ensuring this right now is traffic police manually monitoring the motorcyclists. But due to excess traffic and limited traffic personnels, many violators go unrecognized and continue to practice the same. Thus, it is important to eliminate the human intervention and automate the monitoring system using deep learning and computer vision-based techniques. Our proposed system implements this by extracting number plate of helmet violators and generates an e-challan on the registered mobile number. We propose using a custom trained YOLO-v8 model for violation detection and YOLO-v8 + EasyOCR for number plate detection and extraction. Canny Edge Detection is a preprocessing step that can be used to enhance the edges of objects in an image, making them more distinguishable. This system holds great potential for enhancing safety-related policies and ensuring strict enforcement of traffic regulations. Additionally, it contributes to the advancement of traffic management through the implementation of an AI-based automated traffic violation and ticketing system.

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“…EasyOCR is a Python package for Optical Character Recognition (OCR) that is designed to work with many different languages and scripts [30]. To process an image input, EasyOCR first preprocesses the image by converting it to grayscale and applying some basic filters to enhance the text contrast.…”

Section: Easyocrmentioning

confidence: 99%

Image Caption Generation For Blind Users Of Social Media Websites

SS,

Kalinathan

2023

Preprint

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Emerging fields such as Augmented Reality (AR), Virtual Reality (VR), Ecommerce platforms like Amazon, Ebay etc and Social media sites make use of images with text information for creating immersive experiences, selling products and sharing posts. Generating captions from these images has large potential effects, such as descriptions associated with medical images, text-based image retrieval, information accessed for visually impaired users, human-robot interaction etc. Existing image captioning systems fail to recognize the text on the image which leads to loss of context information such as additional information regarding location, poster contents, product specifications etc. The objective of our proposed system is to design a model that would generate a brief description for a given image at a semantic level using Clip-GPT2 and OCR techniques along with a sentence fusion model BART, for an image with text. Capturing text within images during caption generation outperforms the existing models, with a Rogue value of 81.66. Thus our system helps communicate the contextual information of an image to a visually impaired user as an informative textual description.

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Comparative Analysis of EasyOCR and TesseractOCR for Automatic License Plate Recognition using Deep Learning Algorithm

Cited by 21 publications

References 15 publications

Analysis of Optical Character Recognition using EasyOCR under Image Degradation

Analysis of Optical Character Recognition using EasyOCR under Image Degradation

A comprehensive review on helmet detection and number plate recognition approaches

Image Caption Generation For Blind Users Of Social Media Websites

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