Affine Shape Descriptor Algorithm for Image Matching and Object Recognition in a Digital Image/Algoritmo para clasificación de formas invariante a transformaciones afines para objetos rÃgidos en una imagen digital
Abstract
The use of shape, as a mean to discriminate between object classes extracted from a digital image, is one of the major roles in machine vision. The use of shape has been studied extensively in recent decades, because the shape of the object holds enough information for its correct classification; additionally, the quantity of memory used to store a border is much less than that of the whole region within it. In this paper, a novel shape descriptor is proposed. The algorithm demonstrates that it has useful properties such as: invariance to affine transformations that are applied to the border (e.g., scales, skews, displacements and rotations), stability in the presence of noise, and good differentiability between different object classes. A comparative analysis is included to show the performance of our proposal with respect to the state of the art algorithms.References
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