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Shape Recognition Methods Used for Complex Polygonal Shape Recognition
Abstract
Two new algorithms, optimal and sub-optimal solution algorithm, for shape recognition using geometric calculations are proposed. They are mode-based, which means that shape from the data base which is considered as a model is compared with another shape extracted from the sequence of images, such as, for example, a moving object. The proposed algorithms are efficient and tolerate severe noise. They have the ability to identify the close match between the noisy polygon that has a significantly greater number of sides and the assigned polygon. They work for convex and concave polygons equally well. These algorithms are invariant under translation, rotation, change of scale, and are reasonably easy to compute. The proposed criterion is a metric. The polygonal shapes are compared based on their areas and gravity centers. One polygon is placed over the other one so that one polygon has a fixed center of area (gravity center). The area of the intersection of these two polygons is calculated after one of the polygons is rotated one degree at time. The angular position with the best match is recorded.
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