Paper Info
Title
Open Datasets and Tools for Arabic Text Detection and Recognition in News Video Frames.
Abstract
Recognizing texts in video is more complex than in other environments such as scanned documents. Video texts appear in various colors, unknown fonts and sizes, often affected by compression artifacts and low quality. In contrast to Latin texts, there are no publicly available datasets which cover all aspects of the Arabic Video OCR domain. This paper describes a new well-defined and annotated Arabic-Text-in-Video dataset called AcTiV 2.0. The dataset is dedicated especially to building and evaluating Arabic video text detection and recognition systems. AcTiV 2.0 contains 189 video clips serving as a raw material for creating 4063 key frames for the detection task and 10,415 cropped text images for the recognition task. AcTiV 2.0 is also distributed with its annotation and evaluation tools that are made open-source for standardization and validation purposes. This paper also reports on the evaluation of several systems tested under the proposed detection and recognition protocols.
Year
DOI
Venue
2018
10.3390/jimaging4020032
JOURNAL OF IMAGING
Keywords
Field
DocType
video text detection,video text recognition,AcTiV dataset,Arabic Video OCR
Computer vision,Annotation,Arabic,Compression artifact,Artificial intelligence,Natural language processing,Standardization,Mathematics,Text detection
Journal
Volume
Issue
ISSN
4
2
2313-433X
Citations 
PageRank 
References 
0
0.34
13
Authors
5
Name
Order
Citations
PageRank
Oussama Zayene172.82
Sameh Masmoudi Touj2394.73
Jean Hennebert341738.70
Rolf Ingold475782.40
Najoua Essoukri Ben Amara520941.48