Gandamalla M.D.,GNITS |
Advances in Intelligent Systems and Computing | Year: 2016
Clustering techniques suffer from fact that once they are merged or split, it cannot be undone or refined. Considering the stability of the Genetic Algorithm and the local searching capability of Swarm Optimization in clustering, these two algorithms are combined. Genetic Algorithms, being global search technique, have been widely applied for discovery of clusters. A novel data clustering based on a new optimization scheme which has benefits of high convergence rate and easy implementation method is been proposed were in local minima is disregarded in an intelligent manner. This paper, we intend to apply GA and swarm optimization (i.e., PSO) technique to optimize the clustering. We exemplify our proposed method on real data sets from UCI repository. From experimental results it can be ascertained that combined approach i.e., PSO_GA gives better clustering accuracy compare to PSO-based method. © Springer India 2016.
Kashappa N.,GND Engineering College |
Ramesh Reddy K.,GNITS
Research Journal of Applied Sciences, Engineering and Technology | Year: 2011
This study deals with comparison of 3-level inverter- fed induction motor drive with 9-level inverterfed induction motor drive. A conventional Voltage Source Inverter (VSI) fed induction motor drive is modelled and simulated using matlab simulink and the results are presented. 9-level inverter is also simulated and the corresponding results are presented. The FFT spectrums for the outputs are analyzed to study the reduction in the harmonics. © Maxwell Scientific Organization, 2011.
Dammavalam S.R.,VNRVJIET |
Maddala S.,GNITS |
Krishna Prasad M.H.M.,Jawaharlal Nehru Technological University Anantapur
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2011
Image fusion is a technique to combine the registered images to increase the spatial resolution of acquired low detail multi-sensor images and preserving their spectral information. In fusing panchromatic and multispectral images, the objective is to reduce uncertainty and minimize redundancy in the output while maximizing relevant information. Different fusion methods provide different results for different applications, medical imaging, automatic target guidance system, remote sensing, machine vision, automatic change detection, and biometrics. In this paper, we utilize a fuzzy logic approach to fuse images from different sensors, in order to enhance visualization. The work here further explores the comparison between image fusion using wavelet transform and fuzzy logic approach along with performance/quality evaluation measures like image quality index, entropy, mutual information measure, root mean square error, peak signal to noise ratio, fusion factor, fusion symmetry and fusion index. Experimental results prove that the use of the proposed method can efficiently preserve the spectral information while improving the spatial resolution of the remote sensing images. © 2011 Springer-Verlag.
Hegde G.,SDMIT |
Seetha M.,GNITS |
Seetha M.,Jawaharlal Nehru Technological University |
Hegde N.,VCE Inc
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2015
In this study appearance based facial expression recognition is presented by extracting the Gabor magnitude feature vectors (GMFV) and Gabor Phase Congruency vectors (GPCV). Feature vector space of these two vectors dimensions are reduced and redundant information is removed using subspace methods. Both GMFV and GPCV spaces are projected with Eigen score and projected matching scores are normalized and fused. Final matching score of each subspace method are normalized using Z-score normalization and fused together using maximum rule. Dimension of entire Gabor feature vector space consumes larger area of memory and high processing time with more redundant data. To overcome this problem in this paper entire Gabor matching score level fusion (EGMSLF) approach based on subspace methods is introduced. The JAFFE database is used for experiment. Support vector machine classifier technique is used as classifier. Performance evaluation is carried out by comparing proposed approach with state of art approaches. Proposed EGMSLF approach enhances the performance of earlier methods. © Springer International Publishing Switzerland 2015.
Seetha M.,GNITS |
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2010
Image Classification is the process of assigning classes to the pixels in remote sensed images and important for GIS applications, since the classified image is much easier to incorporate than the original unclassified image. To resolve misclassification in traditional parametric classifier like Maximum Likelihood Classifier, the neural network classifier is implemented using back propagation algorithm. The extra spectral and spatial knowledge acquired from the ancillary information is required to improve the accuracy and remove the spectral confusion. To build knowledge base automatically, this paper explores a non-parametric decision tree classifier to extract knowledge from the spatial data in the form of classification rules. A new method is proposed using a data structure called Peano Count Tree (P-tree) for decision tree classification. The Peano Count Tree is a spatial data organization that provides a lossless compressed representation of a spatial data set and facilitates efficient classification than other data mining techniques. The accuracy is assessed using the parameters overall accuracy, User's accuracy and Producer's accuracy for image classification methods of Maximum Likelihood Classification, neural network classification using back propagation, Knowledge Base Classification, Post classification and P-tree Classifier. The results reveal that the knowledge extracted from decision tree classifier and P-tree data structure from proposed approach remove the problem of spectral confusion to a greater extent. It is ascertained that the P-tree classifier surpasses the other classification techniques. © 2010 Copyright SPIE - The International Society for Optical Engineering.
Sindhuja G.,GNITS |
Renuka Devi S.M.,GNITS
2015 Conference on Power, Control, Communication and Computational Technologies for Sustainable Growth, PCCCTSG 2015 | Year: 2015
Object tracking is a exploring field having a broad collection of applications in actual world. The major steps for tracking a target object include detection of interested moving objects and tracking of such objects from frame to frame in a video. Mean shift based object tracking has received much importance because of its assets such as real time, robust and easy to implement. Advanced versions of this algorithm are developed which differ in template updating for representing target objects in different video sequence. This paper performs comparative analysis of basic mean shift algorithm with two enhanced versions of mean shift i.e., BWH and CBWH. The experimental results on bench mark databases show that CBWH target representation leads to faster convergence and more proper localization than other target representations. © 2015 IEEE.
Saraswathi T.,GNITS |
Ragini K.,GNITS |
Ganapathy Reddy Ch.,GNITS
ICECT 2011 - 2011 3rd International Conference on Electronics Computer Technology | Year: 2011
A new low transition test pattern generator using a linear feedback shift register (LFSR) called LT-LFSR reduce the average and peak power of a circuit during test by generating three intermediate patterns between the random patterns. The goal of having intermediate patterns is to reduce the transitional activities of Primary Inputs (PI) which eventually reduces the switching activities inside the Circuit under Test (CUT) and hence, power consumption. The random nature of the test patterns is kept intact. The area overhead of the additional components to the LFSR is negligible compared to the large circuit sizes. The experimental results for ISCAS'85 and '89 benchmarks, confirm up to 77% and 49% reduction in average and peak power, respectively. © 2011 IEEE.
Bhargavi V.S.,GNITS |
Raju S.V.,Jawaharlal Nehru Technological University Anantapur
Proceedings of the 2016 IEEE International Conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2016 | Year: 2016
A Mobile ad Hoc Network is a collection of nodes which is an infrastructure less network and hence can be easily established and deployed instantly. In addition to their normal operation, all the nodes in this kind of network act as routers as well. Because of the mobility and dynamic nature of the network, all the nodes are free to move randomly and hence topology of a MANET changes very frequently. This invites the complexity of routing the packets from source to destination. Also, as a MANET is a multi-hop network, the packets should pass through intermediate nodes which always need not be genuine all the time which poses many security issues in MANET's. Our paper discusses a secure routing protocol which is a trust based secure routing scheme that considers information collected from neighbouring nodes. Based on the trust information received about a node from its neighbouring nodes and its past history of transactions, we assign a trust value for every node in the network. If this value is less than a specific threshold set by the coordinator nodes, that specific node can be considered as a malicious node and hence routing paths should not involve such nodes, which guarantees secure path routing. This protocol has been implemented on NS-2 and results show that this protocol achieved better performance in terms of the packet delivery ratio and throughput when compared to existing routing schemes in literature. © 2016 IEEE.
Hegde G.P.,SDMIT |
Advances in Intelligent Systems and Computing | Year: 2015
Face recognition is one of the widely used research topic in biometric fields and it is rigorously studied. Recognizing faces under varying facial expressions is still a very challenging task because adjoining of real time expression in a person face causes a wide range of difficulties in recognition systems. Moreover facial expression is a way of nonverbal communication. Facial expression will reveal the sensation or passion of a person and also it can be used to reveal someone’s mental views and psychosomatic aspects. Subspace analysis are the most vital techniques which are used to find the basis vectors that optimally cluster the projected data according to their class labels. Subspace is a subset of a larger space, which contains the properties of the larger space. The key contribution of this article is, we have developed and analyzed the 2 state of the art subspace approaches for recognizing faces under varying facial expressions using a common set of train and test images. This evaluation gives us the exact face recognition rates of the 2 systems under varying facial expressions. This exhaustive analysis would be a great asset for researchers working world-wide on face recognition under varying facial expressions. The train and test images are considered from standard public face databases ATT, and JAFFE. © Springer International Publishing Switzerland 2015.
Rambabu T.,G.N.I.T.S |
Prasad P.V.,C.B.I. T
2014 International Conference on Smart Electric Grid, ISEG 2014 | Year: 2014
This paper proposes a new algorithm for Distributed Generator placement and sizing in radial distribution system based on a novel index. The index is developed considering stable node voltages referred as power stability index (PSI). A new analytic approach is adopted to visualize the impact of DG losses, voltage profile, and voltage stability. The proposed method is tested on 12-bus and 69 bus radial systems. © 2014 IEEE.