A study of shape characterization framework for planar objects from computer vision perspective
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Abstract
Shape is perceived as a unique characteristic of an object which is intuitively understood
newlineyet difficult to define formally. The human perception of shape seems to be an abstract
newlineentity for which all kinds of mathematical frameworks fall short to find a proper crisp
newlinedescription in representing the unique characteristic of a shape. Over the years, researchers
newlinehave been trying to explore multifarious frameworks to characterize the shape of a planar
newlineobject represented as digital bi-level image. In digital geometry, a shape of an object
newlineis usually viewed as a set of connected dots located within a two-dimensional grid.
newlineRegardless of how a shape is viewed, it has always been important visual information
newlineattracting the attention of researchers over the decades for dealing with the problems
newlineof computer vision. With the ever-growing demand for emulation of a human vision
newlinesystem, research interest among today s scientists in the computer vision domain has been
newlinegradually driven towards obtaining maturity in automated image analysis and recognition.
newlineSince many aspects of images in our world are strongly determined by shape based
newlinecharacteristics, the applications of shape characterization extend over almost every applied
newlinescientific and technological area. In spite of its ubiquitous role in multiple applications,
newlinenot many comprehensive shape characterization frameworks are found to be effective
newlinefor offering a desirable solution to the computer vision problems. Existing studies do
newlinenot fill in the vacuum in a comprehensive fashion particularly in developing effective
newlineshape characterization frameworks for the kind of solutions required for today s computer
newlinevision problems. Our effort in this doctoral proposal has been primarily conceived as
newlinedocumenting a study of a few shape characterization frameworks and their abilities in
newlineproviding solutions to various computer vision problems.
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