Abstract
In this paper, we proposed a new shape matrix representation mechanism for the automatic classification of targets from ISAR imagery. The proposed shape matrix representation method overcomes the undesirable side effects associated with the existing methods, such as the quantization of superfluous inner and outer shape details. The proposed mechanism also deals with the variations in shape representations of the targets caused by the erroneous procedure employed by exiting methods for the selection of axis-of-reference. The efficiency and robustness of the proposed mechanism are examined through experimental analysis, and the results are presented.
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Kondaveeti, H.K., Vatsavayi, V.K. (2021). Ameliorated Shape Matrix Representation for Efficient Classification of Targets in ISAR Imagery. In: Bhattacharyya, S., Nayak, J., Prakash, K.B., Naik, B., Abraham, A. (eds) International Conference on Intelligent and Smart Computing in Data Analytics. Advances in Intelligent Systems and Computing, vol 1312. Springer, Singapore. https://doi.org/10.1007/978-981-33-6176-8_20
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DOI: https://doi.org/10.1007/978-981-33-6176-8_20
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