Evaluation for uncertain image classification and segmentation

Authors:
Arnaud Martin;Hicham Laanaya;Andreas Arnold-Bos
Affiliations:
ENSIETA E3I2 EA3876, 2 rue François Verny, 29806 Brest Cedex 09, France;ENSIETA E3I2 EA3876, 2 rue François Verny, 29806 Brest Cedex 09, France and Faculté des Sciences de Rabat, Avenue Ibn Batouta, B.P. 1014 Rabat, Morocco;ENSIETA E3I2 EA3876, 2 rue François Verny, 29806 Brest Cedex 09, France
Venue:
Pattern Recognition
Year:
2006

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Abstract

Each year, numerous segmentation and classification algorithms are invented or reused to solve problems where machine vision is needed. Generally, the efficiency of these algorithms is compared against the results given by one or many human experts. However, in many situations, the location of the real boundaries of the objects as well as their classes are not known with certainty by the human experts. Furthermore, only one aspect of the segmentation and classification problem is generally evaluated. In this paper we present a new evaluation method for classification and segmentation of image, where we take into account both the classification and segmentation results as well as the level of certainty given by the experts. As a concrete example of our method, we evaluate an automatic seabed characterization algorithm based on sonar images.