Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Subject: search.filters.subject.Enhancement

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    Performance evaluation of OCR on poor resolution text document images using different pre processing steps
    (Institute of Electrical and Electronics Engineers Inc., 2015) Naganjaneyulu, G.V.S.S.K.R.; Narasimhadhan, A.V.; Venkatesh, K.
    The performance of optical character recognition (OCR) algorithm is poor on low resolution scanned text images. The conventional low pass filters in L2 space can slightly improve the performance. The method of enhancement of poor resolution text images using a low pass signal filtering algorithm in the weighted Sobolev space results in high pass correction similar to un sharp masking. This can further improve the performance of OCR on low resolution text images. In this paper, the performance of a typical OCR system on low resolution scanned text images, is studied without using any preprocessing step, with low pass filtering in L2 space, and compared with low pass filtering in weighted Sobolev space as pre processing steps. © 2014 IEEE.
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    A Framework for Quality Enhancement of Multispectral Remote Sensing Images
    (Institute of Electrical and Electronics Engineers Inc., 2018) Suresh, S.; Das, D.; Lal, S.
    Researches in satellite image enhancement have been particularly confined to two major areas-contrast enhancement and image de noising of remote sensing images. The processing of relatively dark or shadowed images necessitates the need for robust remote sensing enhancement techniques. In this paper, a robust framework for quality enhancement of multispectral remote sensing images is proposed. The quantitative results of proposed algorithm and other existing remote sensing enhancement algorithms are calculated in terms of DE, NIQMC, BIQME, PisDist and CM on different remote sensing and other image databases. Results reveal that visual enhancement of the proposed algorithm is better than other existing remote sensing enhancement algorithms. Finally, the simulation experimental results show that proposed algorithm is effective and efficient for remotes sensing as well as natural images. © 2017 IEEE.
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    Semi-Analytical Model for Bubble Departure Diameter Prediction for Triangular Grooved Surface
    (Toronto Metropolitan University, 2019) Sathyabhama, A.
    This paper presents experimental studies of pool boiling heat transfer from plain and triangular grooved surfaces to water at atmospheric pressure. Visualization technique is used to investigate the boiling phenomenon using high speed digital camera with image acquisition speed of 1000 fps at resolution of 320 x 240 pixels. It is observed that surface modification with grooves improves the boiling heat transfer. Various aspects of bubble behaviour on plain and grooved surfaces were investigated. The bubble generation frequency was higher for grooved surfaces. The average error in bubble departure diameter prediction of the semi-analytical model developed is 29.22%. © 2019, Toronto Metropolitan University. All rights reserved.
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    A Novel Fingerprint Image Enhancement based on Super Resolution
    (Institute of Electrical and Electronics Engineers Inc., 2020) Muhammed, A.; Pais, A.R.
    Fingerprint is a most common and broadly accepted biometric trait used for personal authentication. In fingerprint-based authentication, the feature extraction module extract features, and these extracted characteristics are used for authentication. In fingerprints, the feature extraction module heavily depends on the status of the image. However, in practice, always getting a good quality fingerprint image is not possible. Moreover, a notable number of fingerprints collected are of poor quality. The accurate extraction of fingerprint characteristics from a lesser quality fingerprint image is a challenging problem. Fingerprint enhancement is introduced to resolve this issue. Hence in this paper, we introduce a fingerprint enhancement technique using a Deep Convolution Neural Network (DCNN), which improves image quality. The proposed method consists of super-resolution, followed by filtering and enhancement. The proposed method provides better results as compared with the conventional fingerprint enhancement methods. The experimental results determine that the proposed strategy improves the visual clarity of low-quality images and reduces the error rates during the fingerprint matching. © 2020 IEEE.