The Effect of Metric Space on the Results of Graph Based Colour Image Segmentation

Abstract

This paper deals with the impact of the metric space on the results of colour image segmentation algorithm. Distance and similarity measures are important tasks for quality of colour image segmentation. Main idea of this research is to make a comparison of algorithm results with using different metrics. Euclidean distance is the most used metric in many colour image segmentation algorithms. This paper shows comparison of this metric with many other metrics. Nine different metrics are gradually used in efficient graph based colour image segmentation algorithm created in the C++ language. The efficiency of precision and recall is one of the investigation tasks of colour image segmentation.