Efficient Keypoint Reduction for Document Image Matching

Thomas Konidaris, Volker Märgner, Hussein Mohammed, H. Stiehl

Abstract

In this paper we propose a method for eliminating SIFT keypoints in document images. The proposed method is applied as a first step towards word spotting. One key issue when using SIFT keypoints in document images is that a large number of keypoints can be found in non-textual regions. It would be ideal if we could eliminate as much as irrelevant keypoints as possible in order to speed-up processing. This is accomplished by altering the original matching process of SIFT descriptors using an iterative process that enables the detection of keypoints that belong to multiple correct instances throughout the document image, which is an issue that the original SIFT algorithm cannot tackle in a satisfactory way. The proposed method manages a reduction over 99% of the extracted keypoints with satisfactory performance.

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Paper Citation


in Harvard Style

Konidaris T., Märgner V., Mohammed H. and Stiehl H. (2019). Efficient Keypoint Reduction for Document Image Matching.In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-351-3, pages 664-670. DOI: 10.5220/0007412006640670


in Bibtex Style

@conference{icpram19,
author={Thomas Konidaris and Volker Märgner and Hussein Mohammed and H. Stiehl},
title={Efficient Keypoint Reduction for Document Image Matching},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2019},
pages={664-670},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007412006640670},
isbn={978-989-758-351-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Efficient Keypoint Reduction for Document Image Matching
SN - 978-989-758-351-3
AU - Konidaris T.
AU - Märgner V.
AU - Mohammed H.
AU - Stiehl H.
PY - 2019
SP - 664
EP - 670
DO - 10.5220/0007412006640670