Amoeba Techniques for Shape and Texture Analysis

Morphological amoebas are image-adaptive structuring elements for morphological and other local image filters introduced by Lerallut et al. Their construction is based on combining spatial distance with contrast information into an image-dependent metric. Amoeba filters show interesting parallels to image filtering methods based on partial differential equations (PDEs), which can be confirmed by asymptotic equivalence results. In computing amoebas, graph structures are generated that hold information about local image texture. This paper reviews and summarises the work of the author and his coauthors on morphological amoebas, particularly their relations to PDE filters and texture analysis. It presents some extensions and points out directions for future investigation on the subject.Comment: 38 pages, 19 figures v2: minor corrections and rephrasing, Section 5 (pre-smoothing) extende

Objective assessment of visual pursuit in patients with disorders of consciousness: an exploratory study.

Visual pursuit is a key marker of residual consciousness in patients with disorders of consciousness (DOC). Currently, its assessment relies on subjective clinical decisions. In this study, we explore the variability of such clinical assessments, and present an easy-to-use device composed of cameras and video processing algorithms that could help the clinician to improve the detection of visual pursuit in a clinical context. Visual pursuit was assessed by an experienced research neuropsychologist on 31 patients with DOC and on 23 healthy subjects, while the device was used to simultaneously record videos of both one eye and the mirror. These videos were then scored by three researchers: the experienced research neuropsychologist who did the clinical assessment, another experienced research neuropsychologist, and a neurologist. For each video, a consensus was decided between the three persons, and used as the gold standard of the presence or absence of visual pursuit. Almost 10% of the patients were misclassified at the bedside according to their consensus. An automatic classifier analyzed eye and mirror trajectories, and was able to identify patients and healthy subjects with visual pursuit, in total agreement with the consensus on video. In conclusion, our device can be used easily in patients with DOC while respecting the current guidelines of visual pursuit assessment. Our results suggest that our material and our classification method can identify patients with visual pursuit, as well as the three researchers based on video recordings can

The isophotic metric and its application to feature sensitive morphology on surfaces

Abstract. We introduce the isophotic metric, a new metric on surfaces, in which the length of a surface curve is not just dependent on the curve itself, but also on the variation of the surface normals along it. A weak variation of the normals brings the isophotic length of a curve close to its Euclidean length, whereas a strong normal variation increases the isophotic length. We actually have a whole family of metrics, with a parameter that controls the amount by which the normals influence the metric. We are interested here in surfaces with features such as smoothed edges, which are characterized by a significant deviation of the two principal curvatures. The isophotic metric is sensitive to those features: paths along features are close to geodesics in the isophotic metric, paths across features have high isophotic length. This shape effect makes the isophotic metric useful for a number of applications. We address feature sensitive image processing with mathematical morphology on surfaces, feature sensitive geometric design on surfaces, and feature sensitive local neighborhood definition and region growing as an aid in the segmentation process for reverse engineering of geometric objects.