Abstract
The paper addresses the problem of rotation and translation invariant recognition of objects described by many features. A new set of rotation invariants features are introduced. Numerical experiments are performed to test the invariance for coloured images and chemical compounds. A comparisons with the other methods are made. The obtained results suggest it is worth to explore the proposed method.
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Everingham, M., Van Gool, L., Williams, C.K.I., Winn, J., Zisserman, A.: The PASCAL visual object classes challenge 2007 (VOC2007) results. http://www.pascal-network.org/challenges/VOC/voc2007/workshop/index.html
Flusser, J.: Moment invariants in image analysis (2005)
Flusser, J., Zitova, B., Suk, T.: Moments and Moment Invariants in Pattern Recognition. Wiley Publishing, New York (2009)
Hu, M.K.: Visual pattern recognition by moment invariants. IRE Trans. Inf. Theory 8(2), 179–187 (1962). https://doi.org/10.1109/TIT.1962.1057692
Klekota, J., Roth, F.P.: Chemical substructures that enrich for biological activity. Bioinformatics 24(21), 2518–2525 (2008). https://doi.org/10.1093/bioinformatics/btn479
Li, D.: Analysis of moment invariants on image scaling and rotation. In: Sobh, T., Elleithy, K. (eds.) Innovations in Computing Sciences and Software Engineering, pp. 415–419. Springer, Netherlands (2010). https://doi.org/10.1007/978-90-481-9112-3_70
Mukundan, R., Ramakrishnan, K.: Moment Functions in Image Analysis: Theory and Applications. World Scientific, Singapore, New Jersey, London (1998)
Murray-Rust, P., Rzepa, H.: XML and Its Application in Chemistry, vol. 2, pp. 466–490. Wiley-VCH, New York (2003)
Chaudhari, A.M.P.R.: Content based image retrieval using color and shape features. Int. J. Adv. Res. Electr. Electron. Instrum. Eng. 1(5), 386–392 (2012)
Rodrigues, M.A. (ed.): Invariants for Pattern Recognition and Classification. World Scientific, Singapore (2000)
Rodríguez-Damián, M., Cernadas, E., Formella, A., de Sá-Otero, P.: Pollen classification using brightness-based and shape-based descriptors. In: 17th International Conference on Pattern Recognition, ICPR 2004, Cambridge, UK, 23–26 August 2004, pp. 212–215 (2004). https://doi.org/10.1109/ICPR.2004.1334098
Singh, S., Jokhan, A., Sharma, B., Lal, S.: An innovative approach of progressive feedback via artificial neural networks. J. Mach. Learn. Technol. 2(1), 64–71 (2011). http://bioinfopublication.org/viewhtml.php?artid=BIA0001170
Tangelder, J.W.H., Veltkamp, R.C.: A survey of content based 3d shape retrieval methods. Multimed. Tools Appl. 39(3), 441–471 (2007). https://doi.org/10.1007/s11042-007-0181-0
Xiao, B., Cui, J., Qin, H., Li, W., Wang, G.: Moments and moment invariants in the radon space. Pattern Recognit. 48(9), 2772–2784 (2015). https://doi.org/10.1016/j.patcog.2015.04.007
Acknowledgments
This research was partially supported by National Centre of Science (Poland) Grants No. 2016/21/N/ST6/01019.
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Wiercioch, M. (2018). On Modeling Objects Using Sequence of Moment Invariants. In: Saeed, K., Homenda, W. (eds) Computer Information Systems and Industrial Management. CISIM 2018. Lecture Notes in Computer Science(), vol 11127. Springer, Cham. https://doi.org/10.1007/978-3-319-99954-8_9
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DOI: https://doi.org/10.1007/978-3-319-99954-8_9
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