Comparative study of contour detection evaluation criteria based on dissimilarity measures

Sébastien Chabrier (1) , Hélène Laurent (2) , Christophe Rosenberger (3) , Bruno Emile (2)

1 JETO - Terre-Océan
2 LVR - Laboratoire Vision et Robotique
3 Equipe SAFE - Laboratoire GREYC - UMR6072

We present in this article a comparative study of well-known supervised evaluation criteria that enable the quantification of the quality of contour detection algorithms. The tested criteria are often used or combined in the literature to create new ones. Though these criteria are classical ones, none comparison has been made, on a large amount of data, to understand their relative behaviors. The objective of this article is to overcome this lack using large test databases both in a synthetic an a real context allowing a comparison in various situations and application fields and consequently to start a general comparison which could be extended by any person interested in this topic. After a review of the most common criteria used for the quantification of the quality of contour detection algorithms, their respective performances are presented using synthetic segmentation results in order to show their performance relevance face to under-segmentation, over-segmentation or situations combining these two perturbations. These criteria are then tested on natural images in order to process the diversity of the possible encountered situations. The used databases and the following study can constitute the ground works for any researcher who wants to confront a new criterion face to well-known ones.

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Sébastien Chabrier, Hélène Laurent, Christophe Rosenberger, Bruno Emile. Comparative study of contour detection evaluation criteria based on dissimilarity measures. EURASIP Journal on Image and Video Processing, 2008, pp.1-10. ⟨hal-00255983⟩