The emphasis of the two approaches described in this chapter is on determining shape skeletons in the presence of noise. The parts of the skeleton which are most robust in the presence of noise correspond to the parts of the shape where its width varies slowly. In contrast, singular points of the skeleton such as junctions tend to be sensitive to noise. The strategy therefore is to concentrate ...

A robust skeleton-based graph matching method for object recognition and recovery applications is presented. The object model uses both a skeleton model and contour segment models, for object recognition and recovery. Initially, the skeleton representation is created from the input contour that is provided by a deformable contour method (DCM). The skeleton is then matched against a set of objec...

BACKGROUND To extract DTI parameters from a specific structure, a region of interest (ROI) must be defined. ROI selection in small structures is challenging; the final measurement results could be affected due to the significant impact of small geometrical errors. In this study the optic tracts were analyzed with the aim to assess differences in DTI parameters due to ROI method and to identify ...

Keywords: Thinning algorithm Robustness against noise Scale space filtering Sketch image preprocessing a b s t r a c t We apply scale space filtering to thinning of binary sketch images by introducing a framework for making thinning algorithms robust against noise. Our framework derives multiple representations of an input image within multiple scales of filtering. Then, the filtering scale tha...

Converting a binary image to a skeleton or medial axis form is often used to preserve the shape details efficiently. The medial axis is converted to a shock graph which has structure like a tree. Shock graphs are derived from the skeleton and have emerged as powerful 2-D shape representation. A skeleton has number of branches. A branch is a connected set of points between an end point and a joi...

We present a pipeline to generate high quality quad dominant meshes for vascular structures from a given volumetric image. As common for medical image segmentation we use a Level Set approach to separate the region of interest from the background. However in contrast to the standard method we control the topology of the deformable object – defined by the Level Set function – which allows us to ...

This paper describes a novel procedure for thinning binary text images by generating graphical representations of words within the image. A smoothed polygonal approximation of the boundaries of each word is ®rst decomposed into a set of contiguous triangles. Each triangle is then classi®ed into one of only three possible types from which a graph is generated that represents the topological feat...

A symbolic image is an array representing a set of objects and a set of spatial relations among them. Symbolic images and related structures have been used in a number of applications including Image Databases, Spatial Reasoning, Path Planning and Spatial Pattern Matching. In this paper we describe a Pictorial Query-By-Example (PQBE) language aimed at the retrieval of direction relations from s...

Human skeleton joints are popular for action analysis since they can be easily extracted from videos to discard background noises. However, current skeleton representations do not fully benefit from machine learning with CNNs. We propose “Skepxels” a spatio-temporal representation for skeleton sequences to fully exploit the “local” correlations between joints using the 2D convolution kernels of...

In this paper, we present a method for correcting a skeleton-based vectorization. The method robustly segments the skeleton of an image into basic features, and uses these features to reconstruct analytically all the junctions. It corrects some of the topological errors usually brought by polygonal approximation methods, and improves the precision of the junction points detection. We rst give s...