Volume : V, Issue : I, January - 2016

PARTICLE SWARM OPTIMIZATION (PSO) BASED K–MEANS IMAGE SEGMENTATION ALGORITHM

P. Pedda Sadhu Naik, Dr. T. Venu Gopal

Abstract :

Image Segmentation plays very significant role in the fields of Digital Image Processing (DIP) for various tasks such as image understanding, image analysis, and pattern recognition etc. In current era, there is an incredible upsurge in the image data samples from every part of the world. Due to this, the necessity to introduce novel technique for an efficient segmentation has also increased.Though there are numerous traditional approaches, the efficiency of segmentation is yet to be increased. Therefore, the author proposed an intelligent based image segmentation approach in this paper. The particle swarm optimization is one of the Swarm Intelligence approach introduced in this paper as the preprocessing technique prior to the image segmentation. The image is preprocessed as to obtain the optimum pixels and then k–means clustering technique is performed on image for segmentation. The accuracy and the efficiency of the suggested methodology is matched with the prevailing k–means clustering algorithm by applying the suggested approach on different types of environmental images.

Keywords :

Article: Download PDF   DOI : 10.36106/ijsr  

Cite This Article:

P.Pedda Sadhu Naik, Dr.T.Venu Gopal Particle Swarm Optimization (PSO) Based K-Means Image Segmentation Algorithm International Journal of Scientific Research, Vol : 5, Issue : 1 January 2016

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