Title :
A comparative study of supervised evaluation criteria for image segmentation
Author :
Chabrier, S. ; Laurent, H. ; Emile, B. ; Rosenberger, C. ; Marche, P.
Author_Institution :
Lab. Vision et Robot., Univ. d´Orleans, Bourges, France
Abstract :
This paper presents a comparative study of five supervised evaluation criteria for image segmentation. The different criteria have been tested on a selection of hundred images extracted from the c Corel database for which manual segmentation results provided by experts are available. Nine segmentation algorithms have been considered, most of which are based on threshold selection. In order to compare the behavior of the different criteria towards over- and undersegmentation, three thresholds have been taken into account, for each selected image, to simulate the various situations. Experimental results permit to reveal the advantages and limitations of the studied criteria.
Keywords :
feature extraction; image segmentation; learning (artificial intelligence); Corel database; image analysis; image segmentation; over-segmentation criteria; supervised evaluation criteria; threshold selection; under-segmentation criteria; Abstracts; Context; Image color analysis; Image segmentation;
Conference_Titel :
Signal Processing Conference, 2004 12th European
Conference_Location :
Vienna
Print_ISBN :
978-320-0001-65-7
