Volume : II, Issue : VI, June - 2013

Adaptive Pillar K–Mean Approach for Image Segmentation

Miki K. Patel , Mitula H. Pandya

Abstract :

Image segmentation is the process of partitioning a digital image into multiple segments. Adaptive K-means clustering algorithm is tries to develop K-means algorithm to obtain high performance and efficiency. This segmentation process includes a new mechanism for solves a selection number by determining the number of clusters using datasets from images by frame size and the absolute value between the means. Pillar algorithm segmentation process includes a new mechanism for clustering the elements of high-resolution images in order to improve precision and reduce execution time. The Pillar algorithm considers the pillars’ placement which should be located as far as possible from each other to withstand against the pressure distribution of a roof, as identical to the number of centroids amongst the data distribution of image. Our research focus on image segmentation by using adaptive k-mean algorithm and pillar k-mean algorithm. This paper mainly focus on improve the segmentation quality in aspects of precision and execution time. The experimental results clarify the effectiveness of our approach to improve image segmentation quality based on precision and computational time using less iteration.

Keywords :

Article: Download PDF   DOI : 10.36106/ijsr  

Cite This Article:

Miki K. Patel , Mitula H. Pandya Adaptive Pillar K-Mean Approach for Image Segmentation International Journal of Scientific Research, Vol : 2, Issue : 6 June 2013

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