Multistage Image Clustering and Segmentation with Normalised Cuts

Normalised cuts algorithm requires massive similarity measurement computation for image segmentation. Since a digital camera at present has the capability to produce high resolution image, it will be inevitably that resizing image into suitable resolution at which the algorithm can perform image segmentation with minimal burden. While retaining the important features in the images, natural images are likely to be restricted for resizing them into a particular smaller resolution. Dividing an image into equal size of regions (named as image cells) for the segmentation is proposed here to solve the problem of missing important features when the image resolution is overly reduced. Gradually, the locally segmented clusters from the image cells are taken for second stage segmentation to merge them up globally. In this paper, experimental results using the mentioned method are shown. Experiment shows that it is capable to produce reasonable segmented clusters based on the proposed approach.