This book constitutes the refereed proceedings of the 6th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition, GbRPR 2007, held in Alicante, Spain in June 2007.

It covers matching, distances and measures, graph-based segmentation and image processing, graph-based clustering, graph representations, pyramids, combinatorial maps and homologies, as well as graph clustering, embedding and learning.

Information theory has proved to be effective for solving many computer vision and pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feature selection, optimal classifier design and many others). Nowadays, researchers are widely bringing information theory elements to the CVPR arena. Among these elements there are measures (entropy, mutual information ), principles (maximum entropy, minimax entropy ) and theories (rate distortion theory, method of types ).

This book explores and introduces the latter elements...