Real object recognition using moment invariants |
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Authors: | Muharrem Mercimek Kayhan Gulez Tarik Veli Mumcu |
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Affiliation: | (1) Electrical Engineering Department, Yildiz Technical University, Electrical-Electronics Faculty, 34349 Besiktas-Istanbul, Turkey |
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Abstract: | Moments and functions of moments have been extensively employed as invariant global features of images in pattern recognition.
In this study, a flexible recognition system that can compute the good features for high classification of 3-D real objects
is investigated. For object recognition, regardless of orientation, size and position, feature vectors are computed with the
help of nonlinear moment invariant functions. Representations of objects using two-dimensional images that are taken from
different angles of view are the main features leading us to our objective. After efficient feature extraction, the main focus
of this study, the recognition performance of classifiers in conjunction with moment-based feature sets, is introduced |
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Keywords: | Regular moment functions 3-D object recognition image processing neural networks fuzzy K-NN |
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