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2017 | OriginalPaper | Chapter

A Fast Method for Scene Text Detection

Authors : Qing Fang, Yanping Yang, Yali Chen, Xiaoyu Yao

Published in: Computer Vision

Publisher: Springer Singapore

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Abstract

Text detection is important for many applications such as text retrieval, blind guidance, and industrial automation. Meanwhile, text detection is a challenging task due to the complexity of the background and the diversity of the font, size and color of the text. In recent years, deep learning achieves good results in image classification and detection, and provides us a new method for text detection. In this paper, a deep learning based detection method – Single Shot MultiBox Detector (SSD) is adopted. But SSD is a general object detection method, not specific for text detection and is not fast enough. Our method aims to develop a network for text detection, improve the speed and reduce the model. Therefore, we design a feature extraction network with the inception module and an additional deconvolution layer. The experiment on benchmark – ICDAR2013 demonstrates that our method is faster than other SSD-based method comparable results.

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Metadata
Title
A Fast Method for Scene Text Detection
Authors
Qing Fang
Yanping Yang
Yali Chen
Xiaoyu Yao
Copyright Year
2017
Publisher
Springer Singapore
Book
Computer Vision

Print ISBN: 978-981-10-7298-7

Electronic ISBN: 978-981-10-7299-4

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-981-10-7299-4_62

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