DocumentCode :
2766049
Title :
A Survey on Skeletons in Digital Image Processing
Author :
Lakshmi, J.K. ; Punithavalli, Mrs M.
Author_Institution :
Dept. of Comput. Sci., SNR SONS Coll., Coimbatore, India
fYear :
2009
fDate :
7-9 March 2009
Firstpage :
260
Lastpage :
269
Abstract :
An image is digitized to convert it to a form which can be stored in a computer\´s memory or on some form of storage media such as a hard disk or CD-ROM. Once the image has been digitized, it can be operated upon by various image processing operations like enhancement, restoration, reconstruction, compression. An image defined in the "real world" is considered to be a function of two real variables, for example, a(x,y) with a as the amplitude (e.g. brightness) of the image at the real coordinate position (x,y). An image may be considered to contain sub-images sometimes referred to as regions-of-interest, ROIs, or simply regions. This concept reflects the fact that images frequently contain collections of objects each of which can be the basis for a region. In a sophisticated image processing system it should be possible to apply specific image processing operations to selected regions. Thus one part of an image (region) might be processed to suppress motion blur while another part might be processed to improve color rendition. For performing image processing operations ,the basic structure called skeleton is much more essential and highly adaptive tool. Skeletons are important shape descriptors in object representation and recognition. A skeleton that captures essential topology and shape information of the object in a simple form is extremely useful in solving various problems such as character recognition, 3D model matching and retrieval, and medical image analysis. Medical imaging systems. Due to its compact shape representation, image skeleton has been studied for a long time in computer vision, pattern recognition, and optical character recognition. It is a powerful tool for intermediate representation for a number of geometric operations on solid models. Many image processing applications depend on the skeletons.
Keywords :
image colour analysis; image motion analysis; image representation; image restoration; image thinning; object recognition; color rendition; computer vision; digital image processing; geometric operations; image compression; image enhancement; image reconstruction; image restoration; image skeleton; motion blur suppression; object recognition; object representation; optical character recognition; pattern recognition; regions-of-interest; shape descriptors; shape representation; solid models; Biomedical imaging; Character recognition; Digital images; Hard disks; Image converters; Image processing; Image storage; Power system modeling; Shape; Skeleton; Shape decomposition; Shape representation; Skeleton; Skeleton quality; Skeletonization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Image Processing, 2009 International Conference on
Conference_Location :
Bangkok
Print_ISBN :
978-0-7695-3565-4
Type :
conf
DOI :
10.1109/ICDIP.2009.21
Filename :
5190619
Link To Document :
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