Inverse correlation filters of objects features with optimized regularization for image processing

Roman Kvуetnyy; Yuriy Bunyak; Olga Sofina; Volodymyr Kotsiubynskyi; Oksana Bezstmertna; Liudmyla Shevchenko; Andrzej Kotyra; Bakhyt Yeraliyeva

doi:10.1117/12.2664497

12 December 2022 Inverse correlation filters of objects features with optimized regularization for image processing

Roman Kvуetnyy, Yuriy Bunyak, Olga Sofina, Volodymyr Kotsiubynskyi, Oksana Bezstmertna, Liudmyla Shevchenko, Andrzej Kotyra, Bakhyt Yeraliyeva

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Proceedings Volume 12476, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2022; 124760Q (2022) https://doi.org/10.1117/12.2664497
Event: Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2022, 2022, Lublin, Poland

Abstract

The problem of extraction of the image objects features by means of using the inverse filters (IF) is considered. The IF are formed by the inversion of the matrix composed of correlation vectors of a set of objects templates examples. The inversion is made with the help of singular value decomposition. Three approaches to regularization and its impact on IF recognition properties are also considered. There was defined the functional that specifies minimal mutual relations between functions of the filters to obtain optimal separation of the features. A training process is used in order to obtain filters with high recognition performance.

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Roman Kvуetnyy, Yuriy Bunyak, Olga Sofina, Volodymyr Kotsiubynskyi, Oksana Bezstmertna, Liudmyla Shevchenko, Andrzej Kotyra, and Bakhyt Yeraliyeva "Inverse correlation filters of objects features with optimized regularization for image processing", Proc. SPIE 12476, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2022, 124760Q (12 December 2022); https://doi.org/10.1117/12.2664497

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