A Segmentation Scheme Based on a Multi-graph Representation: Application to Colour Cadastral Maps
Graphics Recognition. Recent Advances and New Opportunities
Simulation of Ground-Truth Validation Data Via Physically- and Statistically-Based Warps
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
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We present in this article a new unsupervised evaluation criterion that enables the quantification of the quality of an image segmentation result according to the type of the original image. We first briefly present a comparative study of existing unsupervised evaluation criteria. Then, we present a method for the determination of the type of the original image: uniform, mixed or textured by using a learning method (Support Vector Machine). In the third part, we present the proposed algorithm for segmentation evaluation and the experimental results on synthetic images from a large database. Last, we conclude and present some perspectives of this work.