Proposal of statistical method of semantic indexing for multilingual documents

Mallat, Souheyl; Hkiri, Emna; Zrigui, Mounir

doi:10.1109/fuzz-ieee.2016.7737996

Cited by 5 publications

(1 citation statement)

References 12 publications

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“…However, text detection and localization in a video frame is still a challenging problem due to the numerous difficulties resulting from a variety of text features (size, color and style), the presence of complex background and conditions of video acquisition. Although many methods have been proposed to detect embedded text, few methods are designed for text detection in Arabic news videos, due to Arabic language complexity and specific characteristics [8,10,7]. Indeed, the Arabic script is cursive and has various diacritical.…”

Section: Introductionmentioning

confidence: 99%

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

Mansouri¹,

Charhad²,

Zrigui³

2018

CyS

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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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Section: Introductionmentioning

confidence: 99%