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Saravanan D.,IFHE Hyderabad
Pakistan Journal of Biotechnology | Year: 2017

Image processing plays a key role in every human's life today. The use of images has widely increased due to many factors, but technology makes it very easy to upload images from any corner of the world. Information is exchanged via images easily and effectively and is an important mode of communication today. Searching for images on the web has its own advantages as well as disadvantages. The latest technique involves searching the content by using traditional text retrieval, and it never gives any guarantee to find the required information. For searching image content today most of the researchers spend time for creating various indexes to bring the effective result. This research paper brings one image searching technique which uses image feature based searching with the help of image fundamental feature. The experimental results also confirmed that the proposed approach can always retrieve intended targets even with poor selection of initial query points.


Saravanan D.,IFHE Hyderabad
Advances in Intelligent Systems and Computing | Year: 2018

Data mining is a technique the bring out hidden information effectively from an available data set. Most of this extraction works well when performed for binary and character information. Mining information form images is a challenge today for many researchers. Creating of images and videos is easy as it does not require any domain knowledge, but extracting the required knowledge is difficult. For this reason, today video data mining is an interesting area for many researchers. To overcome these problems many researchers are motivated for finding an effective retrieval and indexing technique. This research paper brings a new technique for video content retrieval using hierarchical clustering technique. Objective of this work is to extract image key frames from the trained image set and use this as an image input query. The experiment proved that the proposed technique provided better results than existing video retrieval and indexing technique. © Springer Nature Singapore Pte Ltd. 2018.


Saravanan D.,IFHE Hyderabad
2016 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2016 | Year: 2017

In this paper, multimedia data's are extracted using clustering technique with help of image feature values. The planned frameworks works based on image indexing and retrieval technique it replace a presented object with the retrieval result in real time. Along with this indexing mechanism a histogram-based color descriptors also introduced to reliably capture and represent the color properties of multiple images. Including of this a classification approach is also carried out by the classified associations and by identified with each object identifier. Experimental results verified that proposed technique produced good result of video data content retrieval. © 2016 IEEE.


Saravanan D.,IFHE Hyderabad
2016 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2016 | Year: 2017

Camouflaging of twofold images is necessary while information's are communication through image. Technology brings the communication easier, most of the communication today through open network, for this threats also increased frequently. This paper brings the new technique called flow code procedure technique. Given binary image converted into text representation and encrypted using flow code procedure. The existing image transformation done through image compression, communicate this compress image alone never brings the security. For that images must be converted into code form before it start communicating in the network. Here images are converted as text, using character system table. The main advantage of the proposed technique user no need to remember keys. Experimental outcome proves that proposed technique brings the better result than existing techniques. © 2016 IEEE.


Devaraj S.,IFHE Hyderabad
World Journal of Engineering | Year: 2017

Purpose - Data mining is the process of detecting knowledge from a given huge data set. Among the data set, multimedia is the data which contains diverse data such as audio, video, image, text and motion. In this growing field of video data, mining the video data plays vital role in the field of video data mining. In video data mining, video data are grouped into frames. In this vast amount of video frames, the fast retrieval of needed information is important one. This paper aims to propose a Birch-based clustering method for content-based image retrieval. Design/methodology/approach - In image retrieval system, image segmentation plays a very important role. A text file, normally, is divided into sections, that is, piece, sentences, word and character for this information which are organized and indexed effectively like in a video, the information is dynamic in nature and this information is converted to static for easy retrieval. For this, video files are divided into a number of frames or segments. After the segmentation process, images are trained for retrieval process, and from these, unwanted images are removed from the data set. The noise or unwanted image removal pseudo-code is shown below. In the code image, pixel value represents the value of the difference between the two adjacent image pixel values. By assuming a threshold for the image value, the duplicate images are found. After finding the duplicate image, it is removed from the data set. Clustering is used in many applications as a stand-alone tool to get insight into data distribution and as a pre-processing step for other algorithms (Ester et al., 1996). Specifically, it is used in pattern recognition, spatial data analysis, image processing, economic science document classification, etc. Hierarchical clustering algorithms are classified as agglomerative or divisive. BRICH uses clustering attribute (CA) and clustering feature hierarchy (CA-Hierarchy) for the formation of clusters. It perform multidimensional data objects. Every BRICH algorithm based on the memory-oriented information, that is, memory constrains, is involved in the processing of the data sets. This information is represented in Figures 6-10. For forming clusters, they use the amount of object in the cluster (A), the sum of all points in the data set (S) and need the square value of the all objects (P). Findings - The proposed technique brings an effective result for cluster formation. Originality/value - BRICH uses a novel approach to model the degree of inter-connectivity and closeness between each pair of clusters that takes into account the internal characteristics of the clusters themselves. © Emerald Publishing Limited.


Girish G.P.,IFHE Hyderabad
Energy Strategy Reviews | Year: 2016

In this study we investigate Spot electricity price forecasting performance of Autoregressive-GARCH models on Indian spot electricity price series. Hourly spot electricity price data for each of the five regions of Indian Electricity market from 1st of October 2010 to 15th November 2013 is used for the study to evaluate forecasting performance of the calibrated models. The conditional mean and conditional variance equations are estimated and one-step-ahead forecasts with a rolling window is performed. The fact that India being the only country in the world having power exchanges in-spite of demand outstripping supply and peak power shortage even to this day, further emphasizes the significance and criticality of spot electricity price forecasting from a power market participant's perspective and its practical relevance for Open access consumers in India. © 2016 Elsevier Ltd.


Vaithianathan S.,IFHE Hyderabad
Electronic Commerce Research | Year: 2010

Firms across the globe have adopted e-commerce (EC) in their operations and have reaped benefits thereof. While firms in technologically developed countries like US and UK has deployed EC to its advantage, whereas firms in developing countries like India failed to follow the suit. Though it has been widely acknowledged by the researchers that the adoption of EC by businesses in developing countries is an important economic indicator of growth; many firms in India still have not realized the potential benefits of EC. This study examines the existing status of EC in India and reviews the available literature on E-commerce adoption in India and puts forth opportunities for future research. The study might serve as a starting point for further research in e-commerce in India. © Springer Science+Business Media, LLC 2010.


Saravanan D.,IFHE Hyderabad
Procedia Computer Science | Year: 2016

A video is an effective tool to exchange the information in the structure of showing the brief text message due to the advance developed technology. Video capturing is effortless process but the related video retrieval is the difficult process, for that process the videos must be indexed. Retrieval is the method that retrieved a video using a user query. The query will be image or texts depend upon the query result output system that returned a particular video or image based on that query. In this project we create a indexing for video file by using segment based indexing technique. Here video will be divided into a hierarchy which is in storyboards of film making. For instance, a hierarchical based video search is composed into multi stage abstraction for assist the users to locate the specific video segments/frames logically. This paper brings out the reduced bandwidth and reduced delays the video through the network of searching and reviewing. Experimental results verify this. © 2016 The Authors.


Balaji M.S.,IFHE Hyderabad | Chakrabarti D.,IFHE Hyderabad
Journal of Interactive Online Learning | Year: 2010

The present study contributes to the understanding of the effectiveness of online discussion forum in student learning. A conceptual model based on 'theory of online learning' and 'media richness theory' was proposed and empirically tested. We extend the current understanding of media richness theory to suggest that use of multiple media can enrich the communication context and perceived learning. Hierarchical regression was applied to investigate the relationships between antecedent factors, interaction and perceived learning. The results show that the perceived richness of online discussion forum has significant positive effect on student participation and interaction, and learning, when used along with traditional classroom lecture. Implications of these findings are discussed as they provide important guidelines for management educators.


In this paper we have presented a research for de-noising the EEG collected Brainstem Speech Evoked Potentials data collected in an audiology lab in University of Ottawa, from 10 different human subjects. Here the de-noising techniques we have considered are Yule-Walker Multiband Filter, Cascaded Yule-Walker-Comb Filter, Conventional Wavelet Transform estimation filters: Daubechies, Symlet, Coiflet Wavelet families, Translation Invariant (TI) Wavelet Transform estimation filter, FAST Independent Component Analysis (FASTICA) De-noising Technique, Combined algorithm of "Translation Invariant (TI) Wavelets and Independent Component Analysis" De-noising technique. The performance measures we have considered are Mean Square Error (MSE) and Signal-to-Noise-Ratio (SNR) values. Out of these techniques we found that cascading of Yule-Walker filter and Comb-Peak filter gave better De-noising performance than Yule-Walker Multiband Filter. Then conventional Wavelets performed far better than the cascaded filter, in those Daubechies family of wavelets worked better than all. Then FASTICA Algorithm worked near to the performance of Conventional Wavelets but far better than cascaded filter. Then we have utilized Translation Invariant (TI) wavelet algorithm which provided the excellent performance than above all. Then we have utilized combined Algorithm of "Translation Invariant (TI) Wavelets and Independent Component Analysis - CSTIICA" algorithm which found to be, it may perform better than TI wavelets algorithm. Ultimately TI and CSTIICA algorithms are found to be may be the best auditory artifact removal techniques and can be highly useful in auditory EEG data analysis to the best. © 2015 The Authors.

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