Faculty Publications
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Publications by NITK Faculty
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Item Super resolution of video with sharpened edges using multiple frames - A novel approach(2009) Pais, A.R.; D'Souza, J.; Guddeti, G.R.M.; Patil, S.B.In most electronic video applications, video with Higher Resolution(HR) are often required. HR video can offer more details that may be critical in various applications like Video Surveillance. Super resolution technique refers to generation of high resolution image from low resolution image by adding some extra information. Super resolution allows us to reduce the need of extra hardware to obtain HR image. This paper proposes a new method for super resolution video generation with sharpened edges using multiple frames. Unique information present in subpixel shifted frames is extracted and used for frequency domain registration process. © 2009 IEEE.Item Recent trends in content-based video copy detection(2010) Roopalakshmi, R.; Guddeti, G.R.M.Video copy detection is an interesting & challenging problem, as it is becoming increasingly important with the growing rate of illegal digital media and huge piracy issues. Therefore, in the present era of Internet &Multimedia technologies,the existence of ubiquitous digital videos, has led to the requirement of robust video copy detection techniques, for content management and copyright protection. In this paper, an overview of content based video copy detection (CBVCD) is presented along with the different state-of-the-art techniques used for video feature/ signature description. This article also explores the future key directions and highlights the research challenges that need to be addressed in the CBVCD paradigm. © 2010 IEEE.Item A novel approach to video copy detection using audio fingerprints and PCA(Elsevier B.V., 2011) Roopalakshmi, R.; Guddeti, G.R.M.In Content-Based Copy detection (CBCD) literature, numerous state-of-the-art techniques are primarily focusing on visual content of video. Exploiting audio fingerprints for CBCD problem is necessary, because of following rea-sons: audio content constitutes an indispensable information source; transformations on audio content is limited compared to visual content. In this paper, a novel CBCD approach using audio features and PCA is proposed, which includes two stages: first, multiple feature vectors are computed by utilizing MFCC and four spectral descriptors; second, features are further processed using PCA, to provide compact feature description. The results of experiments tested on TRECVID-2007 dataset, demonstrate the efficiency of proposed method against various transformations. © 2011 Published by Elsevier Ltd.Item Parallelized K-Means clustering algorithm for self aware mobile Ad-hoc networks(2011) Thomas, L.; Manjappa, K.; Annappa, B.; Guddeti, G.R.M.Providing Quality of Service (QoS) in Mobile Ad-hoc Network (MANET) in terms of bandwidth, delay, jitter, throughput etc., is critical and challenging issue because of node mobility and the shared medium. The work in this paper predicts the best effective cluster while taking QoS parameters into account. The proposed work uses K-Means clustering algorithm for automatically discovering clusters from large data repositories. Further, iterative K-Means clustering algorithm is parallelized using Map-Reduce technique in order to improve the computational efficiency and thereby predicting the best effective cluster. Hence, parallel K-Means algorithm is explored for finding the best effective cluster containing the hops which lies in the best cluster with the best throughput in self aware MANET. Copyright © 2011 ACM.Item A comparative performance evaluation of independent component analysis in medical image denoising(2011) Arakeri, M.P.; Guddeti, G.R.M.Medical images are often corrupted by noise arising in image acquisition process. Accurate diagnosis of the disease requires that medical images be sharp, clear and free of noise. Thus, image denoising is one of the fundamental tasks required by medical image analysis. There exist several denoising techniques for medical images like Median, Wavelet, Wiener, Average and Independent component analysis (ICA) filters. The independent component analysis is a statistical and computational technique for revealing hidden factors that underlie sets of random variables, measurements, or signals. In this paper, ICA has been used to separate out noise from the image to provide important diagnostic information to the physician and its usefulness is demonstrated by comparing its performance with other noise filtering methods. The performance of the ICA and other denoising techniques is evaluated using the metrics like Peak Signal-to-Noise Ratio (PSNR), Mean Absolute Error (MAE) and Mean Structural Similarity Index (MSSIM). The ICA based noise filtering technique gives 25.8245 dB of PSNR, 0.7312 of MAE and 0.9120 of SSIM. The experimental results and the performance comparisons show that ICA proves to be the effective method in eliminating noise from the medical image. © 2011 IEEE.Item Efficient video copy detection using simple and effective extraction of color features(2011) Roopalakshmi, R.; Guddeti, G.R.M.In the present Multimedia era, the exponential growth of illegal videos and huge piracy issues increased the importance of Content Based video Copy Detection (CBCD) techniques. CBCD systems require compact and computationally efficient descriptors for detecting video copies. In this paper, we propose a simple and efficient video signature scheme using Dominant Color Descriptors of MPEG-7 standard in order to implement the proposed CBCD task. Experimental results show that the proposed approach yields better detection rates when compared to that of existing approaches, against common transformations like Contrast change, Noise addition, Rotation, Zooming, Blurring etc. Further, evaluation results also prove that our scheme is computationally efficient by supporting substantial reduction in the total computational cost up to the extent of 65% when compared to that of existing schemes. © 2011 Springer-Verlag.Item Compact and efficient CBCD scheme based on integrated color features(2011) Roopalakshmi, R.; Guddeti, G.R.M.Content-Based Copy Detection (CBCD) is an emergent research topic and has been extensively studied recently. Color is one of the most important and easily recognizable features of visual content. To address efficiency and effectiveness issues of CBCD systems, in this article a compact and computationally inexpensive CBCD scheme using MPEG-7 Dominant Color Descriptor is proposed. This paper proposes a novel dominant color extraction technique, which solves the intrinsic problems of existing color clustering techniques. Experimental results show that the proposed scheme improves detection accuracy up to 38%, and also supports significant reduction in total computational cost up to the extent of 91%, when compared with that of existing schemes against various video transformations. © 2011 IEEE.Item Content-Based Video Copy Detection scheme using motion activity and acoustic features(Springer Verlag service@springer.de, 2014) Roopalakshmi, R.; Guddeti, G.R.M.This paper proposes a new Content-Based video Copy Detection (CBCD) framework, which employs two distinct features namely, motion activity and audio spectral descriptors for detecting video copies, when compared to the conventional uni-feature oriented methods. This article focuses mainly on the extraction and integration of robust fingerprints due to their critical role in detection performance. To achieve robust detection, the proposed framework integrates four stages: 1) Computing motion activity and spectral descriptive words; 2) Generating compact video fingerprints using clustering technique; 3) Performing pruned similarity search to speed up the matching task; 4) Fusing the resultant similarity scores to obtain the final detection results. Experiments on TRECVID-2009 dataset demonstrate that, the proposed method improves the detection accuracy by 33.79% compared to the referencemethods. The results also prove the robustness of the proposed framework against different transformations such as fast forward, noise, cropping, picture-inpicture and mp3 compression. © Springer International Publishing Switzerland 2014.Item A GPU framework for sparse matrix vector multiplication(Institute of Electrical and Electronics Engineers Inc., 2014) Bayyapu, B.; Guddeti, G.R.M.; Raghavendra, P.S.The hardware and software evolutions related to Graphics Processing Units (GPUs), for general purpose computations, have changed the way the parallel programming issues are addressed. Many applications are being ported onto GPU for achieving performance gain. The GPU execution time is continuously optimized by the GPU programmers while optimizing pre-GPU computation overheads attracted the research community in the recent past. While GPU executes the programs given by a CPU, pre-GPU computation overheads does exists and should be optimized for a better usage of GPUs. The GPU framework proposed in this paper improves the overall performance of the application by optimizing pre-GPU computation overheads along with GPU execution time. This paper proposes a sparse matrix format prediction tool to predict an optimal sparse matrix format to be used for a given input matrix by analyzing the input sparse matrix and considering pre-GPU computation overheads. The sparse matrix format predicted by the proposed method is compared against the best performing sparse matrix formats posted in the literature. The proposed model is based on the static data that is available from the input directly and hence the prediction overhead is very small. Compared to GPU specific sparse format prediction, the proposed model is more inclusive and precious in terms of increasing overall application's performance. © 2014 IEEE.Item Ember: A smartphone web browser interface for the blind(Association for Computing Machinery, 2014) Jassi, I.S.; Ruchika, S.; Pulakhandam, S.; Mukherjee, S.; Ashwin, T.S.; Guddeti, G.R.M.Ember is a smartphone web browser interface designed exclusively for the blind user. The Ember keypad enables blind users to type using their knowledge of Braille. The interface is intuitive to the blind user because the layout consists of a very few large targets and remains consistent throughout the application. The verbal command option provides another dimension for user-interface interaction. Twelve out of thirteen users found that Ember verbal command navigation was easier than using a traditional web browser. Ten out of thirteen users found it faster to use the Ember tactile method of navigation compared to a traditional web browser. The learning rate for both the tactile and verbal command methods was faster compared to the learning rate associated with a traditional web browser layout. Finally it was seen that five out of five users found it significantly faster to use the Ember keypad compared to the QWERTY keypad. © 2014 ACM.