CONTOUR DETECTION USING BINARY PARTITION TREES

Contour detection is a hard, challenging, and of paramount importance problem in image processing. State-of-the-art algorithms are approaching human performance but usually entail complex and tailored image models and arduous training. Binary Partition Tree is a hierarchical region-based image model that has been proven to have a wide range of applications in image filtering, information retrieval, object detection, etc. In this paper we propose a contour detection technique based on this versatile image model, extracting the contour information available in the tree yet outperforming one of the most widely-used contour detector.