Image Compression Using Partitioning Around Medoids Clustering Algorithm
Clustering is a unsupervised learning technique. This paper presents a clustering based technique that may be applied to Image compression. The proposed technique clusters all the pixels into predetermined number of groups and produces a representative color for each group. Finally for each pixel only clusters number is stored during compression. This technique can be obtained in machine learning which one of the best methods for clustering is. The k-medoids algorithm is a clustering algorithm related to the K-means algorithm and the medoidshift algorithm.
Keywords: Data Mining, K-medoids clustering, Machine learning, Image compression
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ABOUT THE AUTHORS
Valmik B Nikam
Valmik B Nikam is a Ph.D. candidate in the Department of Computer Technology at Veermata Jijabai Technological Institute, Matunga, Mumbai. He holds B.E. in Computer Science and Engineering from Government College of Engineering Aurangabad and M.E. in Computer Technology from Veermata Jijabai Technological Institute, Mumbai. He worked at Dr. Babasaheb Ambedkar Technological University, Lonere for several years before joining PhD program. His research interests are data mining, scalable computing, image processing. He is a member of CSI, ACM and IEEE.
Vinod J Kadam
Vinod J Kadam is a faculty in Information Technology Deaprtment at Dr. Babasaheb Ambedkar Technological University, Lonere, Raigad District, Maharashtra, India. He Holds BE, and MTech in Information Technology. He has seven years of academic experience. His research interests are in the domain of Data Mining, Image Processing.
B.B.Meshram
B.B.Meshram is a Professor and Head of Department of Computer Technology Department of Veermata Jijabai Technological Institute, Matunga, Mumbai. His current research includes database technologies, data mining, securities, forensic analysis, video processing, distributed computing. His has authored over 150 research publications. He has given numerous invited talks at various conferences, workshops, training programs and also served as chair/co-chair for many conferences/workshops in the area of computer science and engineering.
Valmik B Nikam
Valmik B Nikam is a Ph.D. candidate in the Department of Computer Technology at Veermata Jijabai Technological Institute, Matunga, Mumbai. He holds B.E. in Computer Science and Engineering from Government College of Engineering Aurangabad and M.E. in Computer Technology from Veermata Jijabai Technological Institute, Mumbai. He worked at Dr. Babasaheb Ambedkar Technological University, Lonere for several years before joining PhD program. His research interests are data mining, scalable computing, image processing. He is a member of CSI, ACM and IEEE.
Vinod J Kadam
Vinod J Kadam is a faculty in Information Technology Deaprtment at Dr. Babasaheb Ambedkar Technological University, Lonere, Raigad District, Maharashtra, India. He Holds BE, and MTech in Information Technology. He has seven years of academic experience. His research interests are in the domain of Data Mining, Image Processing.
B.B.Meshram
B.B.Meshram is a Professor and Head of Department of Computer Technology Department of Veermata Jijabai Technological Institute, Matunga, Mumbai. His current research includes database technologies, data mining, securities, forensic analysis, video processing, distributed computing. His has authored over 150 research publications. He has given numerous invited talks at various conferences, workshops, training programs and also served as chair/co-chair for many conferences/workshops in the area of computer science and engineering.
