Clustering Algorithm in Normalised Cuts Based Image Segmentation

Normalised cut method has been effectively used for image segmentation by representing an image as weighted graph in global view. It does segmentation via partitioning the graphs into sub-graphs. Clustering algorithm is implemented such that sub-graphs with common similarities are grouped together into one cluster and separates sub-graphs that are dissimilar into distinctive clusters. Clustered segments from the normalised cuts are then produced. As the clusters initialisation gives influence to the segmentation result, optimisation of the clustering algorithm is implemented to achieve better segmentation. With the approach applied in the normalised cuts based image segmentation, the constraint of using normalised cuts algorithm in image segmentation can be alleviated. In this paper, evaluation of the clustering algorithm with the normalised cuts image segmentation on images has been carried out and the effect of different image complexity towards normalised cuts segmentation process is presented.