Analysis Of Image Segmentation Approaches With Emphasis On Performance Evaluation Criteria

Many techniques for segmenting images have been developed over the past decade. Proponents of each of the techniques feel that their method is the best, but this is generally based on subjective criteria. This paper reports progress on an effort to develop a set of factors which will allow an objective evaluation of segmenter performance on a comparative basis by analyzing the performance of several segmentation approaches on a common data base. Three generically distinct segmentation approaches were analyzed and their performance measured using the criteria selected. A comparison of techniques based on the results of the test showed the relative performance to be consistent with intuitive expectations. The greatest potential for refining this evaluation approach appears to be in the areas of selection and quantification of the data base and expansion of the set of factors.