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Distance Transform Based Active Contour Approach for Document Image Rectification | IEEE Conference Publication | IEEE Xplore

Distance Transform Based Active Contour Approach for Document Image Rectification


Abstract:

Digitization of document images using OCR based systems is adversely affected if the image of the document contains distortion (warping). Often, costly and precisely cali...Show More

Abstract:

Digitization of document images using OCR based systems is adversely affected if the image of the document contains distortion (warping). Often, costly and precisely calibrated special hardware such as stereo cameras, laser scanners, etc. are used to infer the 3D model of the distorted image which is used to remove the distortion. Recent methods focus on creating a 3D shape model based on the 2D document image. The performance of these methods is highly dependent on estimating an accurate 2D distortion grid. In the domain of printed document images, the white space between the text lines carries as much information about the 2D distortion as the text lines themselves. Based on this intuitive idea, we build a 2D distortion grid from white space lines, which can be used to rectify a printed document image by a Dewar ping algorithm. These white space lines are extracted using a propagation technique on the distance transform of the binarized document image, guided by an open active contour algorithm. We compare our proposed method against a state-of-the-art 2D distortion grid construction method and obtain better results. We also present qualitative and quantitative evaluations for the proposed method.
Date of Conference: 05-09 January 2015
Date Added to IEEE Xplore: 23 February 2015
Electronic ISBN:978-1-4799-6683-7
Print ISSN: 1550-5790
Conference Location: Waikoloa, HI, USA
Citations are not available for this document.

1. Introduction

Optical character recognition (OCR) is an important step in the process of digitizing important documents such as old historic books. OCR research over the last few decades has led to highly accurate digitization of documents. However there is a severe drop in the performance of OCR systems in the presence of distortion (warping) in the scanned/photographed document image as shown in Fig. 1. These systems rely on the document image being planar and having straight horizontal text lines. Therefore, it is critical to remove any distortion that might exist in the document image.

Examples of distortions: (a) Distortion at book bindings, (b) Perspective projection in camera captured image. (c) One of the applications of proposed method: Mobile document scanner (image from google).

Cites in Papers - |

Cites in Papers - IEEE (1)

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1.
Shaodi You, Yasuyuki Matsushita, Sudipta Sinha, Yusuke Bou, Katsushi Ikeuchi, "Multiview Rectification of Folded Documents", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.40, no.2, pp.505-511, 2018.

Cites in Papers - Other Publishers (3)

1.
Pu Li, Weize Quan, Jianwei Guo, Dong-Ming Yan, "Layout-aware Single-image Document Flattening", ACM Transactions on Graphics, vol.43, no.1, pp.1, 2024.
2.
Baraka Jacob Maiseli, "Optimum design of chamfer masks using symmetric mean absolute percentage error", EURASIP Journal on Image and Video Processing, vol.2019, no.1, 2019.
3.
Baraka Jacob Maiseli, LiFei Bai, Xianqiang Yang, Yanfeng Gu, Huijun Gao, "Robust cost function for optimizing chamfer masks", The Visual Computer, vol.34, no.5, pp.617, 2018.

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References

References is not available for this document.