Informatics Publishing Limited

D. Kesavaraja ¹, R. Balasubramanian ², R. S. Rajesh ², D. Sasireka ³

Affiliations
1 Department of Computer Science and Engineering, Dr. Sivanthi Aditanar College of Engineering, Tamil Nadu, IN
2 Department of Computer Science and Engineering, Manonmaniam Sundaranar University, Tamil Nadu, IN
3 Department of Information Technology, Jayamatha Engineering College, Tamil Nadu, IN

Abstract

This paper presents efficient and portable implementations of a useful image segmentation technique which makes use of the faster and a variant of the conventional connected components algorithm which we call parallel Components. In the Modern world majority of the doctors are need image segmentation as the service for various purposes and also they expect this system is run faster and secure. Usually Image segmentation Algorithms are not working faster. In spite of several ongoing researches in Conventional Segmentation and its Algorithms might not be able to run faster. So we propose a cluster computing environment for parallel image Segmentation to provide faster result. This paper is the real time implementation of Distributed Image Segmentation in Clustering of Nodes. We demonstrate the effectiveness and feasibility of our method on a set of Medical CT Scan Images. Our general framework is a single address space, distributed memory programming model. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. The image segmentation algorithm makes use of an efficient cluster process which uses a novel approach for parallel merging. Our experimental results are consistent with the theoretical analysis and practical results. It provides the faster execution time for segmentation, when compared with Conventional method. Our test data is different CT scan images from the Medical database. More efficient implementations of Image Segmentation will likely result in even faster execution times.

Keywords

Parallel Algorithms, Region Growing, Image Enhancement, Image Segmentation, Parallel Performance.

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D. Kesavaraja ¹, R. Balasubramanian ², D. Jeyabharathi ³, D. Sasireka ⁴

Affiliations
1 Department of Computer Science and Engineering, Dr Sivanthi Aditanar College of Engineering, Tiruchendur, Tamilnadu, IN
2 Department of Computer Science and Engineering, Manonmaniam Sundarnar University, Abishekapatti, Tirunelveli, Tamilnadu, IN
3 Department of Computer Science and Engineering, Einstein College of Engineering, Tirunelveli, Tamilnadu, IN
4 Department of Information Technology, PSN College of Engineering and Technology, Tirunelveli, Tamilnadu, IN

Abstract

Cloud computing provides ample opportunity in many areas such as fastest image transmission, secure and efficient imaging as a service. In general users needs faster and secure service. Usually Image Compression Algorithms are not working faster. In spite of several ongoing researches, Conventional Compression and its Algorithms might not be able to run faster. So, we perform comparative study of three image compression algorithm and their variety of features and factors to choose best among them for cluster processing. After choosing a best one it can be applied for a cluster computing environment to run parallel image compression for faster processing. This paper is the real time implementation of a Distributed Image Compression in Clustering of Nodes. In cluster computing, security is also more important factor. So, we propose a Distributed Intrusion Detection System to monitors all the nodes in cluster . If an intrusion occur in node processing then take an prevention step based on RIC (Robust Intrusion Control) Method. We demonstrate the effectiveness and feasibility of our method on a set of satellite images for defense forces. The efficiency ratio of this computation process is 91.20.

Keywords

Compression, Cluster, JPEG, Distributed Computing, Security.

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