Artigo Acesso aberto Revisado por pares

Open Datasets and Tools for Arabic Text Detection and Recognition in News Video Frames

2018; Multidisciplinary Digital Publishing Institute; Volume: 4; Issue: 2 Linguagem: Inglês

10.3390/jimaging4020032

ISSN

2313-433X

Autores

Oussama Zayene, Sameh Masmoudi Touj, Jean Hennebert, Rolf Ingold, Najoua Essoukri Ben Amara,

Tópico(s)

Video Analysis and Summarization

Resumo

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.

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