Text extraction from natural scene image: A survey

148Citations
Citations of this article
161Readers
Mendeley users who have this article in their library.
Get full text

Abstract

With the increasing popularity of portable camera devices and embedded visual processing, text extraction from natural scene images has become a key problem that is deemed to change our everyday lives via novel applications such as augmented reality. Text extraction from natural scene images algorithms is generally composed of the following three stages: (i) detection and localization, (ii) text enhancement and segmentation and (iii) optical character recognition (OCR). The problem is challenging in nature due to variations in the font size and color, text alignment, illumination change and reflections. This paper aims to classify and assess the latest algorithms. More specifically, we draw attention to studies on the first two steps in the extraction process, since OCR is a well-studied area where powerful algorithms already exist. This paper offers to the researchers a link to public image database for the algorithm assessment of text extraction from natural scene images. © 2013 Elsevier B.V.

Cite

CITATION STYLE

APA

Zhang, H., Zhao, K., Song, Y. Z., & Guo, J. (2013). Text extraction from natural scene image: A survey. Neurocomputing, 122, 310–323. https://doi.org/10.1016/j.neucom.2013.05.037

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free