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A new approach for upscaling document images for improving their quality

Pandey, RK and Maiya, SR and Ramakrishnan, AG (2018) A new approach for upscaling document images for improving their quality. In: 14th IEEE India Council International Conference, INDICON 2017, 15 - 17 December 2017, Roorkee.

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Official URL: https://doi.org/10.1109/INDICON.2017.8487796


One of the issues faced by optical character recognition (OCR) softwares is the input document images being not of good quality. So research into the methods of enhancing the document images, before presenting them to OCR softwares, is of utmost importance. The objective is to demonstrate a method of generating a high resolution document image, given a low resolution image. We propose a new method for improving the spatial resolution of document images. Here, we have built a deep neural network based model that utilizes the traditional interpolation methods, takes the best features from them and reconstructs a high resolution image from these features. This is achieved using a convolutional neural network (CNN). The CNN learns a high resolution patch from a corresponding low resolution patch, as a weighted non-linear combination of the outputs of different interpolation techniques. We call our technique as nonlinear fusion of multiple interpolations (NFMI). The NFMI method ensures that the model learns only the best features that can be extracted from all the interpolation techniques combined together. The use of traditional interpolation methods makes sure that the NFMI technique is not computationally expensive. Results on test images show a relative improvement of 54 in word recognition accuracy by OCR over the best interpolation technique for doubling the spatial resolution and 33 for quadrupling the resolution.

Item Type: Conference Paper
Publication: 2017 14th IEEE India Council International Conference, INDICON 2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Additional Information: The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords: Deep learning; Deep neural networks; Feature extraction; Image reconstruction; Image resolution; Interpolation; Neural networks; Optical character recognition, Convolutional Neural Networks (CNN); Document images; High resolution image; Interpolation method; Interpolation techniques; Low resolution images; Optical character recognition (OCR); Super resolution, Image enhancement
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 03 Aug 2022 06:34
Last Modified: 03 Aug 2022 06:34
URI: https://eprints.iisc.ac.in/id/eprint/75209

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