Results 11 to 20 of about 5,692 (199)
ADOCRNet: A Deep Learning OCR for Arabic Documents Recognition
IEEE AccessIn recent years, Optical character recognition (OCR) has experienced a resurgence of interest especially for contemporary Arabic data. In fact, OCR development for printed and handwritten Arabic script is still a challenging task.
Lamia Mosbah +5 more
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A Survey of OCR in Arabic Language: Applications, Techniques, and Challenges
Applied Sciences, 2023 Optical character recognition (OCR) is the process of extracting handwritten or printed text from a scanned or printed image and converting it to a machine-readable form for further data processing, such as searching or editing. Automatic text extraction
Safiullah Faizullah +3 more
doaj +1 more source
برامج التعرف الضوئى على الحروف العربیة : دراسة تقییمیة مقارنة لأغراض استرجاع المعلومات [PDF]
المجلة الدولية لعلوم المكتبات والمعلومات, 2019 In recent times ,There were many Arab digitization projects for theirinformation resources, such as: digital repository of Egyptian university theses,and the digitization of information resources at Dar Al-Kutub in Egypt andanother Arabic projects.
د. عادل نبیل على
doaj +1 more source
A REVIEW OF ARABIC TEXT RECOGNITION DATASET
Asia-Pacific Journal of Information Technology and Multimedia, 2020 Building a robust Optical Character Recognition (OCR) system for languages, such as Arabic with cursive scripts, has always been challenging. These challenges increase if the text contains diacritics of different sizes for characters and words.
Idris Saleh Al-Sheikh +2 more
doaj +1 more source
Advances and Limitations in Open Source Arabic-Script OCR: A Case Study
Digital Studies, 2021 This work presents an accuracy study of the open source OCR engine, Kraken, on the leading Arabic scholarly journal, al-Abhath. In contrast with other commercially available OCR engines, Kraken is shown to be capable of producing highly accurate Arabic ...
Benjamin Kiessling +3 more
doaj +2 more sources
Arabic Documents Information Retrieval for Printed, Handwritten, and Calligraphy Image
IEEE Access, 2021 This paper presents a new computational backend model that supports Arabic document information retrieval (ADIR) as a dataset and OCR services. Therefore, different services that support document analysis, retrieving, processing including dataset ...
Hassanin M. Al-Barhamtoshy +3 more
doaj +1 more source
Segmentation-based, omnifont printed Arabic character recognition without font identification
Journal of King Saud University: Computer and Information Sciences, 2022 Optical Character Recognition OCR is an essential part of many real-world applications such as digital archiving, automatic number plate recognition, handle cheques, etc.
Aziz Qaroush +3 more
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TLWSR: Weakly supervised real‐world scene text image super‐resolution using text label
IET Image Processing, Volume 17, Issue 9, Page 2780-2790, 20 July 2023., 2023 To reduce dependencies on expensive and rare paired real‐world text images, a novel weak supervision framework named TLWSR is designed. Given a subset of HR labels in the training set, text recognition network CRNN and CTC loss with text labels are employed to assist in the super‐resolution of text images.
Qin Shi +3 more
wiley +1 more source
Text detection method based on HDBNet in natural scenes
The Journal of Engineering, Volume 2023, Issue 1, January 2023., 2023 Abstract To solve the problem of large expansion offset of text detection in natural scenes, a text detection method based on HDBNet is proposed. First, the probability map of the text region is obtained by segmenting the image. The binary map is obtained by using the differentiable binarization of the probability map.
Li Wang, Xiang Yao, Chenwei Song
wiley +1 more source
Journal of Sensors, Volume 2023, Issue 1, 2023., 2023 Digital handwritten recognition is an emerging field in optical character recognition (OCR). A digital writing pad replaces manual writing. In digital writing, the alphabet changes in font and shape. During OCR recognition, covert text file errors occur due to digital pen pressure and digital pen position on the digital pad by the writer.
V. Jayanthi, S. Thenmalar, Huan Liu
wiley +1 more source