Text extraction using OCR: A Systematic Review

Mittal, Rishabh; Garg, Anchal

doi:10.1109/icirca48905.2020.9183326

Cited by 46 publications

(13 citation statements)

References 14 publications

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“…Transym OCR [19] is an open source easy for integration OCR tool that supports 45 languages and supports some additional features as automatic orientation detection.…”

Section: B Optical Character Recognitionmentioning

confidence: 99%

An Approach to Engineering Drawing Organization: Title Block Detection and Processing

et al. 2024

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During the last 20 years the world has been meeting digitalization challenges in many areas of life and business. Companies convert their business processes to digital form as much as possible, what allows reducing costs and increasing profits. The paper considers a case of the company aimed at manufacturing and servicing spare parts for mining equipment. The company has collected a large amount of engineering drawings in a paper form that need to be organized in a digital form to simplify and support quick access to these documents. We propose an approach to engineering drawing organization based on modern artificial intelligence technologies for detection of main engineering drawing elements as well as extracting metadata from them. Based on the metadata we propose organizing engineering drawings into a structured digital collection with a possibility of quick access to them. All metadata in drawings are usually located in the title block. We show how we detect the title block as well as process it and recognize needed text-based information. The open-source Google Tesseract framework is used for text recognition in English, Finnish, Spanish, and Portuguese languages. For Cyrillic text recognition our own neural network-based model has been developed and trained on Russian GOST engineering drawings. We developed a drawing organization service and evaluated it based on the company engineering drawings database. The evaluation shows a good accuracy for documents that have a good quality (about 74% for title block detection as well as metadata identification).

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“…Transym OCR [19] is an open source easy for integration OCR tool that supports 45 languages and supports some additional features as automatic orientation detection.…”

Section: B Optical Character Recognitionmentioning

confidence: 99%

An Approach to Engineering Drawing Organization: Title Block Detection and Processing

et al. 2024

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“…To take full advantage of the text information embedded in video frames, the second approach uses optical character recognition (OCR) or existing speech recognition techniques to extract the text data (Kumar et al, 2022; Mittal & Garg, 2020). The use of OCR has two main benefits: it can enrich the information that describes the video content, and it can be used to match certain video segments, rather than the entire video sequence.…”

Section: Computer Science Studiesmentioning

confidence: 99%

A survey of online video advertising

Zhang

Yan

et al. 2023

WIREs Data Min & Knowl

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With the development of social media and the ubiquity of the Internet, recent years have witnessed the rapid development of online video advertising among publishers and advertisers. Video advertising, as a new type of advertisement, has gained significant research attention from both academia and industry, coinciding with the ever-growing volume of online videos. In this research, we provide a comprehensive survey of online video advertising in the fields of social science and computer science. We investigate state-of-the-art articles from 1990 to the present and provide a new taxonomy of extant research topics based on these articles. We also highlight the factors that cause advertising to affect people and the most popular video advertising techniques used in computer science. Finally, on the basis of the analytics of the surveyed papers, future challenges are identified and potential solutions to these are discussed.

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“…In a systematic review of OCR titled "Text extraction using OCR," advancements in machine-printed OCR, such as CNN, LSTM, and SRLSA, show promising improvements in detection rates. The focus remains on the Latin script, with continuous development and expansion of OCR into various sectors [4]. A survey on post-OCR processing shows a significant increase in context-dependent approaches, which is crucial in improving OCR development by evaluating output accuracy and performance [5].…”

Section: Ocr Quality On Researchersmentioning

confidence: 99%

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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Text extraction using OCR: A Systematic Review

Cited by 46 publications

References 14 publications

An Approach to Engineering Drawing Organization: Title Block Detection and Processing

An Approach to Engineering Drawing Organization: Title Block Detection and Processing

A survey of online video advertising

Analysis of Optical Character Recognition using EasyOCR under Image Degradation

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