Title: Analysis of Different Approaches of Parallel Block Processing for K-Means Clustering Algorithm,
Abstract: Distributed Computation has been a recent trend in engineering research.
Parallel Computation is widely used in different areas of Data Mining, Image
Processing, Simulating Models, Aerodynamics and so forth. One of the major
usage of Parallel Processing is widely implemented for clustering the satellite
images of size more than dimension of 1000x1000 in a legacy system. This paper
mainly focuses on the different approaches of parallel block processing such as
row-shaped, column-shaped and square-shaped. These approaches are applied for
classification problem. These approaches is applied to the K-Means clustering
algorithm as this is widely used for the detection of features for high
resolution orthoimagery satellite images. The different approaches are
analyzed, which lead to reduction in execution time and resulted the influence
of improvement in performance measurement compared to sequential K-Means
Clustering algorithm.