In this survey we review the image processing literature on the various approaches and models investigators have used for texture. These include statistical approaches of autocorrelation function, optical transforms, digital transforms, textural edgeness, structural element, gray tone cooccurrence, run lengths, and autoregressive models. We discuss and generalize some structural approaches to texture based on more complex primitives than gray tone. We conclude with some structural-statistical generalizations which apply the statistical techniques to the structural primitives.

Statistical and structural approaches to texture

Two border following algorithms are proposed for the topological analysis of digitized binary images. The first one determines the surroundness relations among the borders of a binary image. Since the outer borders and the hole borders have a one-to-one correspondence to the connected components of 1-pixels and to the holes, respectively, the proposed algorithm yields a representation of a binary image, from which one can extract some sort of features without reconstructing the image. The second algorithm, which is a modified version of the first, follows only the outermost borders (i.e., the outer borders which are not surrounded by holes). These algorithms can be effectively used in component counting, shrinking, and topological structural analysis of binary images, when a sequential digital computer is used.

Topological Structural Analysis of Digitized Binary Images by Border Following

A comprehensive survey of thinning methodologies is presented. A wide range of thinning algorithms, including iterative deletion of pixels and nonpixel-based methods, is covered. Skeletonization algorithms based on medial axis and other distance transforms are not considered. An overview of the iterative thinning process and the pixel-deletion criteria needed to preserve the connectivity of the image pattern is given first. Thinning algorithms are then considered in terms of these criteria and their modes of operation. Nonpixel-based methods that usually produce a center line of the pattern directly in one pass without examining all the individual pixels are discussed. The algorithms are considered in great detail and scope, and the relationships among them are explored. >

Thinning methodologies-a comprehensive survey

https://scholars.cityu.edu.hk/files/26420751/Doube_2010UKPMC.pdf

BoneJ: Free and extensible bone image analysis in ImageJ.

Three-dimensional (3-D) structural parameters derived from lower-dimensional measurements using indirect morphometric methods may be strongly biased if the measured objects deviate from the assumed structure model. With the introduction of 3-D microscopic measuring techniques it is possible to obtain a complete depiction of complex spatial structures. As a consequence, new 3-D methods have recently been developed for the estimation of morphometric parameters such as volume, surface area and connectivity by direct processing of the 3-D images. Structure thickness is an important morphometric parameter which is usually defined for specific structure models only. In this paper we propose a general thickness definition for arbitrary structures allowing us to calculate the mean structure thickness and the thickness distribution of 3-D objects in a direct way and independently of an assumed structure model. Additionally, an efficient implementation for the practical usage of the method is described using distance transformation. The new method is applied to trabecular bone structures measured with a 3-D micro-computed tomography system.

A new method for the model-independent assessment of thickness in three-dimensional images

New algorithms for euclidean distance transformation of an n-dimensional digitized picture with applications

Automatic segmentation of head MRI images by knowledge guided thresholding.

An Analysis of Topological Properties of Digitized Binary Pictures Using Local Features

This paper describes a method for the automated anatomical labeling of the bronchial branch extracted from a three-dimensional (3-D) chest X-ray CT image and its application to a virtual bronchoscopy system (VBS). Automated anatomical labeling is necessary for implementing an advanced computer-aided diagnosis system of 3-D medical images. This method performs the anatomical labeling of the bronchial branch using the knowledge base of the bronchial branch name. The knowledge base holds information on the bronchial branch as a set of rules for its anatomical labeling. A bronchus region is automatically extracted from a given 3-D CT image. A tree structure representing the essential structure of the extracted bronchus is recognized from the bronchus region. Anatomical labeling is performed by comparing this tree structure of the bronchus with the knowledge base. As an application, the authors implemented the function to automatically present the anatomical names of the branches that are shown in the currently rendered image in real time on the VBS. The result showed that the method could segment about 57% of the branches from CT images and extracted a tree structure of about 91% in branches in the segmented bronchus. The anatomical labeling method could assign the correct branch name to about 93% of the branches in the extracted tree structure. Anatomical names were appropriately displayed in the endoscopic view.

Jun-ichiro Toriwaki

Papers

New algorithms for euclidean distance transformation of an n-dimensional digitized picture with applications

Automatic segmentation of head MRI images by knowledge guided thresholding.

An Analysis of Topological Properties of Digitized Binary Pictures Using Local Features

Automated anatomical labeling of the bronchial branch and its application to the virtual bronchoscopy system

Tracking of a bronchoscope using epipolar geometry analysis and intensity-based image registration of real and virtual endoscopic images.