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Moving Target Detection Under Turbulence Degraded Visible and Infrared Image Sequences Read chapter Read first chapter

2018 | OriginalPaper | Chapter

A Novel Text Localization Scheme for Camera Captured Document Images

Authors : Tauseef Khan, Ayatullah Faruk Mollah

Published in: Proceedings of 2nd International Conference on Computer Vision & Image Processing

Publisher: Springer Singapore

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Abstract

In this paper, a hybrid model for detecting text regions from scene images as well as document image is presented. At first, background is suppressed to isolate foreground regions. Then, morphological operations are applied on isolated foreground regions to ensure appropriate region boundary of such objects. Statistical features are extracted from these objects to classify them as text or non-text using a multi-layer perceptron. Classified text components are localized, and non-text ones are ignored. Experimenting on a data set of 227 camera captured images, it is found that the object isolation accuracy is 0.8638 and text non-text classification accuracy is 0.9648. It may be stated that for images with near homogenous background, the present method yields reasonably satisfactory accuracy for practical applications.

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Metadata
Title
A Novel Text Localization Scheme for Camera Captured Document Images
Authors
Tauseef Khan
Ayatullah Faruk Mollah
Copyright Year
2018
Publisher
Springer Singapore
Book
Proceedings of 2nd International Conference on Computer Vision & Image Processing

Print ISBN: 978-981-10-7894-1

Electronic ISBN: 978-981-10-7895-8

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-7895-8_20