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

A fast parallel thinning algorithm is proposed in this paper It consists of two subiterations: one aimed at deleting the south-east boundary points and the north-west corner points while the other one is aimed at deleting the north-west boundary points and the south-east corner points End points and pixel connectivity are preserved Each pattern is thinned down to a skeleton of unitary thickness Experimental results show that this method is very effective 12 references

A fast parallel algorithm for thinning digital patterns

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

Digital topology deals with the topological properties of digital images: or, more generally, of discrete arrays in two or more dimensions. It provides the theoretical foundations for important image processing operations such as connected component labeling and counting, border following, contour filling, and thinning—and their generalizations to three- (or higher-) dimensional “images.” This paper reviews the fundamental concepts of digital topology and surveys the major theoretical results in the field. A bibliography of almost 140 references is included.

Digital topology: introduction and survey

Two parallel thinning algorithms are presented and evaluated in this article. The two algorithms use two-subiteration approaches: (1) alternatively deleting north and east and then south and west boundary pixels and (2) alternately applying a thinning operator to one of two subfields. Image connectivities are proven to be preserved and the algorithms' speed and medial curve thinness are compared to other two-subiteration approaches and a fully parallel approach. Both approaches produce very thin medial curves and the second achieves the fastest overall parallel thinning.

Parallel thinning with two-subiteration algorithms

If a picture contains elongated objects of different thicknesses, one can make measurements on it which are thickness-invariant by first transforming it so that each object is thinned down to a \"medial line\" of constant thickness. Several algorithms are described which perform such a thinning transformation when applied to the picture in parallel. It is proved that these algorithms do not change the connectivity properties of the picture.

R. Stefanelli

Papers

Some Parallel Thinning Algorithms for Digital Pictures