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Kumaraswamy, Y. S.
- A Boosting Frame Work for Improved Content Based Image Retrieval
Abstract Views :755 |
PDF Views:154
Authors
Affiliations
1 Department of CSE, Sathyabama University, Chennai, IN
2 Dept. of MCA, Dayananda Sagar College of Engineering, Bangalore, IN
1 Department of CSE, Sathyabama University, Chennai, IN
2 Dept. of MCA, Dayananda Sagar College of Engineering, Bangalore, IN
Source
Indian Journal of Science and Technology, Vol 6, No 4 (2013), Pagination: 4312-4316Abstract
This paper deals with medical image retrieval for retrieving images similar to query images from a database. Retrieval of archived digital medical images is always a challenge that is still being researched all the more so as such images are of paramount importance in patient diagnosis, therapy, surgical planning, medical reference, and medical training. This paper proposes using the Discrete Sine Transform (DST) for relevant feature extraction, and applies Boosting classification techniques to locate the relevant images. In this study, the boosting is used with J48 and decision stump. Experimental results show that the classification accuracy achieved is fairly goodKeywords
Content Based Image Retrieval (CBIR), Medical Images, Discrete Sine Transform (DST), Boosting, J48, Decision StumpFull Text
References
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- Liu Y, Rong J et al. (2010). A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval pattern analysis and machine intelligence, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol 32(1), 30–44.
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- Quellec G (2010). Medical Case Retrieval From a Committee of Decision Trees IEEE Transactions on Information Technology in Biomedicine, vol 14(5), 1227–1235.
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- Active Contour Based Medical Image Segmentation and Compression using Biorthogonal Wavelet and Embedded Zerotree
Abstract Views :644 |
PDF Views:170
Authors
Affiliations
1 Sathyabama University, Chennai, Tamilnadu
2 Department of MCA, DSCE, Bangalore, Karnataka
1 Sathyabama University, Chennai, Tamilnadu
2 Department of MCA, DSCE, Bangalore, Karnataka
Source
Indian Journal of Science and Technology, Vol 6, No 4 (2013), Pagination: 4390-4395Abstract
This paper addresses medical image compression, as more and more medical images are digitized, economical and effective data compression technologies are needed to minimize the storage volume of medical database in hospitals. In this paper, the Region of Interest (ROI) - representing the diseased part - in a medical image is segmented using active contours. The ROI extracted are then compressed using lossless compression to maintain the integrity. A novel Biorthogonal wavelet and Embedded ZeroTree (EZW) is proposed for compression technique. Experimental results demonstrate that the proposed method significantly improves the Peak Signal to Noise Ratio (PSNR) for the medical image compression.Keywords
Medical Images, Image Compression, Region of Interest, Active Contour, Biorthogonal Wavelets, Embedded ZeroTree (EZW)Full Text
References
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- Performance Evaluation of Web-services Classification
Abstract Views :157 |
PDF Views:0
Authors
Affiliations
1 Department of CSE, Sathyabama University Chennai, IN
2 Department of MCA, Dayananda Sagar College of Engineering, Bangalore, IN
1 Department of CSE, Sathyabama University Chennai, IN
2 Department of MCA, Dayananda Sagar College of Engineering, Bangalore, IN
Source
Indian Journal of Science and Technology, Vol 7, No 10 (2014), Pagination: 1674-1681Abstract
To predict web service quality, based on quality attributes set, experiments were carried out on QWS dataset. This study investigates the efficiency of web service classifiers.Keywords
FURIA, k Nearest Neighbor (kNN), RIDOR, Support Vector Machine (SVM), Web Services, QWS DatasetFull Text
- Vehicle Tracking System and Minimization of Dead Mileage
Abstract Views :180 |
PDF Views:4
This paper proposes an enhanced tracking system to track buses and dynamic calculation of the bus arrival time, considering the effect of traffic on the delay of arrival time using a prediction based model, also reducing the effect of dead mileage on the transportation system using Wireless Sensor Network (WSN). Speed of bus is used to calculate the arrival time dynamically and in turn controls the frequency of bus service.
Authors
Affiliations
1 Dept. of Computer Science, PES Institute of Technology, Bangalore, IN
2 Dayanand Sagar College of Engineering, Bangalore, IN
1 Dept. of Computer Science, PES Institute of Technology, Bangalore, IN
2 Dayanand Sagar College of Engineering, Bangalore, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 2, No 8 (2010), Pagination: 179-183Abstract
Vehicle Tracking System or Automatic Vehicle Location System (AVL) is now one of the most popular technological changes in all over the world that is going to make our personal and business life lot easier. As the term suggests, it enables one to track or monitor the location of vehicle in instant time. Primarily, the system functions with the help of different technologies like the Global Positioning System (GPS), traditional cellular network such as Global System for Mobile Communications (GSM) and other radio frequency medium. But GPS is more effective and accurate in this field.This paper proposes an enhanced tracking system to track buses and dynamic calculation of the bus arrival time, considering the effect of traffic on the delay of arrival time using a prediction based model, also reducing the effect of dead mileage on the transportation system using Wireless Sensor Network (WSN). Speed of bus is used to calculate the arrival time dynamically and in turn controls the frequency of bus service.
