Data, protocol and algorithms for performance evaluation of text detection in Arabic news video

Benchmark datasets and their corresponding evaluation protocols are commonly used by the computer vision community, in a variety of application domains, to assess the performance of existing systems. Even though text detection and recognition in video has seen much progress in recent years, relatively little work has been done to propose standardized annotations and evaluation protocols especially for Arabic Video-OCR systems. In this paper, we present a framework for evaluating text detection in videos. Additionally, dataset, ground-truth annotations and evaluation protocols, are provided for Arabic text detection. Moreover, two published text detection algorithms are tested on a part of the AcTiV database and evaluated using a set of the proposed evaluation protocols.