Automatic Detection of Pomegranate Fruits Using K-means Clustering

Nowadays in agriculture the labour work is very important. This paper is proposed to reduce the labour work in fruit picking by using the image clustering algorithm in a machine vision system. For plucking fruits such as citrus, apple, jujube, etc., so many different classification techniques were proposed. This paper focus on the automatic detection of the pomegranate fruits in an orchard. The image is segmented based on the color feature using k-means clustering algorithm. The K-Means algorithm produces accurate segmentation results only when applied to images defined by homogenous regions with respect to texture and color. Segmentation begins by clustering the pixels based on their color and spatial features. The clustered blocks are then merged to a specific number of regions. Thus it provides a solution for image retrieval. Thus our paper proposes the simulation results that has been attained using the algorithm.