MapReduce Based Text Detection in Big Data Natural Scene Videos

被引：14

作者：

Ben Ayed, Abdelkarim ^{[1
]}

Ben Halima, Mohamed ^{[1
]}

Alimi, Adel M. ^{[1
]}

机构：

[1] Univ Sfax, ENIS, REs Grp Intelligent Machines, REGIM Lab, Sfax 3038, Tunisia

来源：

INNS CONFERENCE ON BIG DATA 2015 PROGRAM | 2015年 / 53卷

关键词：

video text detection; MapReduce; big data;

D O I：

10.1016/j.procs.2015.07.297

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Text detection is a basic step in many computer vision applications including video Optical Character Recognition (OCR), video indexation, understanding video content, etc. Actually, several sources such as mobile devices, monitoring cameras and social networks are generating every day billions of videos with different formats and uncertainty. Such videos require new methods to apply text detection. In this paper, we are introducing a novel text detection technique using many blocks coming from frame decomposition. Each block is analyzed and classified which allowed the extraction of text coordinates using MapReduce programming model. To validate our approach, we test it on YouTube Video Text (YVT) dataset and we found that the running speed of this approach can be more than 2 times as fast as classic approach.

引用

页码：216 / 223

页数：8

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