Hierarchical segmentation is a multi-scale analysis of an image and provides a series of
simplifying nested partitions. Such a hierarchy is rarely an end by itself and requires external …

Using simple grouping rules in Gestalt theory, one may detect higher level features
(geometric structures) in an image from elementary features. By recursive grouping of …

This paper addresses the problem of the supervised assessment of hierarchical region-
based image representations. Given the large amount of partitions represented in such …

Quantitative approaches are part of the understanding of contour integration and the Gestalt
law of good continuation. The present study introduces a new quantitative approach based …

Edge detection remains an active problem in the image processing community, because of
the high complexity of natural images. In the last decade, Desolneux et al. proposed a novel …

We present a novel segmentation algorithm based on a hierarchical representation of
images. The main contribution of this work is to explore the capabilities of the a contrario …

We introduce a new algorithm that allows the detection of line segments, contours, corners
and T-junctions. The proposed model is inspired by the mammal visual system. The …

This paper proposes a new automated hierarchical segmentation method with introduced
relaxation factors for processing high-resolution remote sensing imagery, which aims to …

Hierarchical region-based image representations are versatile tools for segmentation,
filtering, object detection, etc. The evaluation of their spatial accuracy has been usually …

In this paper, we reconsider the early computer vision bottom-up program, according to
which higher level features (geometric structures) in an image could be built up recursively …