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Authors: Chuen-Min Huang ; Yi-Ling Chuang ; Rih-Wei Chang and Ya-Yun Chen

Affiliation: National Yunlin University of Science and Technology, Taiwan

Keyword(s): Image Pre-processing, Text Recognition, Optical Character Recognition (OCR), M-Library Services, Mobile Devices.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing

Abstract: Facing the popularity of web searching, libraries continuously invest in the provision of online searching and refurnish physical facilities to attract users during the past decades. In this study, we conducted a technical feasibility study to facilitate library services by applying a novel image pre-processing technique to enhance performance of OCR via mobile devices. In the binarization stage, a grayscale image is usually assigned a global threshold value to be binary, while this will not be suitable for some scenarios, such as non-uniform lightness and complicated background. Instead of segregating the grayscale image into many regions like other studies, our approach only partitioned an image into three equal-sized horizontal segments to identify the local threshold value of each segment and then restored the three segments back to the original state. The experimental results illustrate that the proposed method efficiently and effectively improves the text recognition. The accur acy rate was raised from 17.7% to 72.05% of all test images. Without counting eight unrecognizable images, the average accuracy rates of our treatment can reach 90.06%. To compare with other studies we conducted another evaluation to examine the validity of our approach. The result showed that our treatment outperforms most of the other studies and the performance achieves 74.6% in precision and 80.2% in the recall.We are confident that this design will not only bring users more convenience in using libraries but help library staff and businessmen to manage the status of books. (More)

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Paper citation in several formats:
Huang, C.; Chuang, Y.; Chang, R. and Chen, Y. (2014). Enhance Text Recognition by Image Pre-Processing to Facilitate Library Services by Mobile Devices. In Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-015-4; ISSN 2184-433X, SciTePress, pages 453-460. DOI: 10.5220/0004818504530460

@conference{icaart14,
author={Chuen{-}Min Huang. and Yi{-}Ling Chuang. and Rih{-}Wei Chang. and Ya{-}Yun Chen.},
title={Enhance Text Recognition by Image Pre-Processing to Facilitate Library Services by Mobile Devices},
booktitle={Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2014},
pages={453-460},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004818504530460},
isbn={978-989-758-015-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Enhance Text Recognition by Image Pre-Processing to Facilitate Library Services by Mobile Devices
SN - 978-989-758-015-4
IS - 2184-433X
AU - Huang, C.
AU - Chuang, Y.
AU - Chang, R.
AU - Chen, Y.
PY - 2014
SP - 453
EP - 460
DO - 10.5220/0004818504530460
PB - SciTePress