In shape analysis, skeleton (or topological skeleton) of a shape is a thin version of that shape that is equidistant to its boundaries. The skeleton usually emphasizes geometrical and topological properties of the shape, such as its connectivity, topology, length, direction, and width. Together with the distance of its points to the shape boundary, the skeleton can also serve as a representation of the shape (they contain all the information necessary to reconstruct the shape).
Skeletons have several different mathematical definitions in the technical literature, and there are many different algorithms for computing them. Various different variants of skeleton can also be found, including straight skeletons, morphological skeletons, etc.
In the technical literature, the concepts of skeleton and medial axis are used interchangeably by some authors, [1] [2] while some other authors [3] [4] [5] regard them as related, but not the same. Similarly, the concepts of skeletonization and thinning are also regarded as identical by some, [2] and not by others. [3]
Skeletons are widely used in computer vision, image analysis, pattern recognition and digital image processing for purposes such as optical character recognition, fingerprint recognition, visual inspection or compression. Within the life sciences skeletons found extensive use to characterize protein folding [6] and plant morphology on various biological scales. [7]
Skeletons have several different mathematical definitions in the technical literature; most of them lead to similar results in continuous spaces, but usually yield different results in discrete spaces.
In his seminal paper, Harry Blum [8] of the Air Force Cambridge Research Laboratories at Hanscom Air Force Base, in Bedford, Massachusetts, defined a medial axis for computing a skeleton of a shape, using an intuitive model of fire propagation on a grass field, where the field has the form of the given shape. If one "sets fire" at all points on the boundary of that grass field simultaneously, then the skeleton is the set of quench points, i.e., those points where two or more wavefronts meet. This intuitive description is the starting point for a number of more precise definitions.
A disk (or ball) B is said to be maximal in a set A if
One way of defining the skeleton of a shape A is as the set of centers of all maximal disks in A. [9]
The skeleton of a shape A can also be defined as the set of centers of the discs that touch the boundary of A in two or more locations. [10] This definition assures that the skeleton points are equidistant from the shape boundary and is mathematically equivalent to Blum's medial axis transform.
Many definitions of skeleton make use of the concept of distance function, which is a function that returns for each point x inside a shape A its distance to the closest point on the boundary of A. Using the distance function is very attractive because its computation is relatively fast.
One of the definitions of skeleton using the distance function is as the ridges of the distance function. [3] There is a common mis-statement in the literature that the skeleton consists of points which are "locally maximum" in the distance transform. This is simply not the case, as even cursory comparison of a distance transform and the resulting skeleton will show. Ridges may have varying height, so a point on the ridge may be lower than its immediate neighbor on the ridge. It is thus not a local maximum, even though it belongs to the ridge. It is, however, less far away vertically than its ground distance would warrant. Otherwise it would be part of the slope.
There are many different algorithms for computing skeletons for shapes in digital images, as well as continuous sets.
Skeletonization algorithms can sometimes create unwanted branches on the output skeletons. Pruning algorithms are often used to remove these branches.
In geometry, the convex hull, convex envelope or convex closure of a shape is the smallest convex set that contains it. The convex hull may be defined either as the intersection of all convex sets containing a given subset of a Euclidean space, or equivalently as the set of all convex combinations of points in the subset. For a bounded subset of the plane, the convex hull may be visualized as the shape enclosed by a rubber band stretched around the subset.
Mathematical morphology (MM) is a theory and technique for the analysis and processing of geometrical structures, based on set theory, lattice theory, topology, and random functions. MM is most commonly applied to digital images, but it can be employed as well on graphs, surface meshes, solids, and many other spatial structures.
Digital geometry deals with discrete sets considered to be digitized models or images of objects of the 2D or 3D Euclidean space. Simply put, digitizing is replacing an object by a discrete set of its points. The images we see on the TV screen, the raster display of a computer, or in newspapers are in fact digital images.
A distance transform, also known as distance map or distance field, is a derived representation of a digital image. The choice of the term depends on the point of view on the object in question: whether the initial image is transformed into another representation, or it is simply endowed with an additional map or field.
The Level-set method (LSM) is a conceptual framework for using level sets as a tool for numerical analysis of surfaces and shapes. LSM can perform numerical computations involving curves and surfaces on a fixed Cartesian grid without having to parameterize these objects. LSM makes it easier to perform computations on shapes with sharp corners and shapes that change topology. These characteristics make LSM effective for modeling objects that vary in time, such as an airbag inflating or a drop of oil floating in water.
A point is said to be equidistant from a set of objects if the distances between that point and each object in the set are equal.
Pickover stalks are certain kinds of details to be found empirically in the Mandelbrot set, in the study of fractal geometry. They are so named after the researcher Clifford Pickover, whose "epsilon cross" method was instrumental in their discovery. An "epsilon cross" is a cross-shaped orbit trap.
The pruning algorithm is a technique used in digital image processing based on mathematical morphology. It is used as a complement to the skeleton and thinning algorithms to remove unwanted parasitic components (spurs). In this case 'parasitic' components refer to branches of a line which are not key to the overall shape of the line and should be removed. These components can often be created by edge detection algorithms or digitization. Common uses for pruning include automatic recognition of hand-printed characters. Often inconsistency in letter writing creates unwanted spurs that need to be eliminated for better characterization.
In computer vision and image processing, a feature is a piece of information about the content of an image; typically about whether a certain region of the image has certain properties. Features may be specific structures in the image such as points, edges or objects. Features may also be the result of a general neighborhood operation or feature detection applied to the image. Other examples of features are related to motion in image sequences, or to shapes defined in terms of curves or boundaries between different image regions.
The medial axis of an object is the set of all points having more than one closest point on the object's boundary. Originally referred to as the topological skeleton, it was introduced in 1967 by Harry Blum as a tool for biological shape recognition. In mathematics the closure of the medial axis is known as the cut locus.
NeuronStudio was a non-commercial program created at Icahn School of Medicine at Mount Sinai by the Computational Neurobiology and Imaging Center. This program performed automatic tracing and reconstruction of neuron structures from confocal image stacks. The resulting models were then exported to a file using standard formats for further processing, modeling, or for statistical analyses. NeuronStudio handled morphologic details on scales spanning local Dendritic spine geometry through complex tree topology to the gross spatial arrangement of multi-neuron networks. Its capability for automated digitization avoided the subjective errors inherent in manual tracing. The program ceased to be supported in 2012 and the project pages were eventually removed from the ISMMS Website. Its documentation and the Windows source code however are still available via the Internet Archive.
Digital topology deals with properties and features of two-dimensional (2D) or three-dimensional (3D) digital images that correspond to topological properties or topological features of objects.
In image processing, ridge detection is the attempt, via software, to locate ridges in an image, defined as curves whose points are local maxima of the function, akin to geographical ridges.
In geometry, a straight skeleton is a method of representing a polygon by a topological skeleton. It is similar in some ways to the medial axis but differs in that the skeleton is composed of straight line segments, while the medial axis of a polygon may involve parabolic curves. However, both are homotopy-equivalent to the underlying polygon.
In digital image processing, morphological skeleton is a skeleton representation of a shape or binary image, computed by means of morphological operators.
In computational geometry and geometric graph theory, a β-skeleton or beta skeleton is an undirected graph defined from a set of points in the Euclidean plane. Two points p and q are connected by an edge whenever all the angles prq are sharper than a threshold determined from the numerical parameter β.
In image processing, the grassfire transform is the computation of the distance from a pixel to the border of a region. It can be described as "setting fire" to the borders of an image region to yield descriptors such as the region's skeleton or medial axis. Harry Blum introduced the concept in 1967.
In mathematics, an abstract cell complex is an abstract set with Alexandrov topology in which a non-negative integer number called dimension is assigned to each point. The complex is called “abstract” since its points, which are called “cells”, are not subsets of a Hausdorff space as is the case in Euclidean and CW complexes. Abstract cell complexes play an important role in image analysis and computer graphics.
Franz-Erich Wolter is a German computer scientist, chaired professor at Leibniz University Hannover, with research contributions especially in computational (differential) geometry and haptic/tactile Virtual reality.
Discrete Skeleton Evolution (DSE) describes an iterative approach to reducing a morphological or topological skeleton. It is a form of pruning in that it removes noisy or redundant branches (spurs) generated by the skeletonization process, while preserving information-rich "trunk" segments. The value assigned to individual branches varies from algorithm to algorithm, with the general goal being to convey the features of interest of the original contour with a few carefully chosen lines. Usually, clarity for human vision is valued as well. DSE algorithms are distinguished by complex, recursive decision-making processes with high computational requirements. Pruning methods such as by structuring element (SE) convolution and the Hough transform are general purpose algorithms which quickly pass through an image and eliminate all branches shorter than a given threshold. DSE methods are most applicable when detail retention and contour reconstruction are valued.