Thinning plays a crucial role in image analysis and pattern recognition applications. It is one
of the most frequently used pre-processing methods to analyze different types of images …

Thinning is one of the most important techniques in the field of image processing. It is
applied to erode the image of an object layer-by-layer until a skeleton is left. Several …

Thinning is an important process in several applications of computer vision. It aims to find
the onepixel midline of the pattern in binary image. In spite of different thinning methods that …

Image thinning is the most essential pre-processing technique that plays major role in image
processing applications such as image analysis and pattern recognition. It is a process that …

A perfectly parallel thinning algorithm (PPTA) is proposed. It can generate perfect skeletons,
which consist of end points, break points, and hole points only. Experimental results show …

Thinning is basically reducing a 'thick'digital object to 'thin'skeleton. Thinning is one of the
most frequently used methods to know the geometrical feature of objects. For example, the …

Thinning algorithms have been used in pattern recognition and image analysis for a long
time. They reduce a binary digital pattern to obtain a unit width skeleton which retains …

Thinning is a very important preprocessing step for many image analysis operations, such
as optical character recognition and fingerprint recognition. The main drawbacks of …

Thinning algorithms are applied in image processing to compute a skeleton of an image. In
this paper a new thinning method is presented which differs in its approach from other …

Thinning or skeletonization is a process for reducing foreground regions in a binary image to
a skeletal remnant that largely preserves the extent and connectivity of the original region …