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From Pattern Recognition to Image Understanding

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Artificial Intelligence and Soft Computing (ICAISC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10245))

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Abstract

This paper shows the trend in the transformation of the classic image recognition via the interpretation of the image content towards automatic shape and image understanding. The approach presented combines the mechanism proposed by Tadeusiewicz in [1] with the theory of granular computing introduced by Pedrycz in [2]. Its name, active partitions, is related to active contour techniques, from which it originates. It provides the ability to transfer the well-known concepts of object localization from the pixel level to image representations with meaningful image granules. Thus, the approach offers a great potential for the development of human-like image content interpretation.

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Acknowledgement

This project has been partly funded with support from the National Science Centre, Republic of Poland, decision number DEC-2012/05/D/ST6/03091. The authors would like to also express their gratitude to the Department of Radiology of the Barlicki University Hospital in Lodz for making medical images available.

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Correspondence to Arkadiusz Tomczyk .

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Szczepaniak, P.S., Tomczyk, A. (2017). From Pattern Recognition to Image Understanding. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10245. Springer, Cham. https://doi.org/10.1007/978-3-319-59063-9_53

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  • DOI: https://doi.org/10.1007/978-3-319-59063-9_53

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  • Online ISBN: 978-3-319-59063-9

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