Arabic Text Detection in News Video Based on Line Segment Detector

Mansouri, Sadek; Charhad, Mbarek; Zrigui, Mounir

doi:10.13053/rcs-132-1-9

Cited by 11 publications

(4 citation statements)

References 14 publications

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“…In image-based OCR, the system receives a single image as input and outputs a single editable text file. In the video-based OCR, the temporal information from different frames is used to recognize the text [19,36]. The exact text appears in a sequence of frames; therefore, the text repetition boosts the recognition accuracy.…”

Section: Image and Video-based Ocrmentioning

confidence: 99%

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Arabic Optical Character Recognition: A Review

Alghyaline¹

2023

Computer Modeling in Engineering &Amp; Sciences

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This study aims to review the latest contributions in Arabic Optical Character Recognition (OCR) during the last decade, which helps interested researchers know the existing techniques and extend or adapt them accordingly. The study describes the characteristics of the Arabic language, different types of OCR systems, different stages of the Arabic OCR system, the researcher's contributions in each step, and the evaluation metrics for OCR. The study reviews the existing datasets for the Arabic OCR and their characteristics. Additionally, this study implemented some preprocessing and segmentation stages of Arabic OCR. The study compares the performance of the existing methods in terms of recognition accuracy. In addition to researchers' OCR methods, commercial and open-source systems are used in the comparison. The Arabic language is morphologically rich and written cursive with dots and diacritics above and under the characters. Most of the existing approaches in the literature were evaluated on isolated characters or isolated words under a controlled environment, and few approaches were tested on pagelevel scripts. Some comparative studies show that the accuracy of the existing Arabic OCR commercial systems is low, under 75% for printed text, and further improvement is needed. Moreover, most of the current approaches are offline OCR systems, and there is no remarkable contribution to online OCR systems.

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Section: Image and Video-based Ocrmentioning

confidence: 99%

“…Most of the existing OCR systems work on Latin, Japanese, Chinese, and Korean scripts [18]. Many authors mentioned that few efforts were made in Arabic OCR compared with Latin and English scripts [19,20]. During the last decade, there has been dramatic advancement in the development of Graphics Processing Units (GPUs).…”

Section: Introductionmentioning

confidence: 99%

Arabic Optical Character Recognition: A Review

Alghyaline¹

2023

Computer Modeling in Engineering &Amp; Sciences

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“…The projection vector is represented by an histogram. In general, baseline position is determined by the central peak -BLSD: In our pervious works [11,12], we propose a new method for basline estimation called Blsd (bsaline estimation based on line segment detector). In a first step,line segment for each word has been detected using LSD method which is proposed by Grompone et al [6].…”

Section: Comparative Study For Baseline Estimationmentioning

confidence: 99%

A Heuristic Approach to Detect and Localize Text on Arabic News Video

Mansouri¹,

Charhad²,

Zrigui³

2018

CyS

Self Cite

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Automatic text detection in video sequences remains a challenging problem due to the variety of sizes, colors and the presence of complex background. In this paper, we attempt to solve this problem by proposing a robust detection-validation schema for text localization in Arabic news video. Candidate text regions are first detected by using a hybrid method which combines MSER detector and edge information. Then, these regions are grouped using morphological operators. Finally, a verification process is applied to remove noisy non-text regions including specific features for Arabic text. Performance and efficacy of the proposed text detection approach have been tested By using Arabic-Text-in-Video database (AcTiV-DB).

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“…In the last stage, commercial OCR engine ABBYY FineReader has been applied for the recognition of text news. More details are shown in our papers [10] [11].…”

Section: A Level 1:low-level Processingmentioning

confidence: 99%