Abstract
Based on the properties of Template Matching and Radon Transform, a new Multi-Shape Invariant Radon Transform (MSIRT) is proposed in this paper. Unlike Radon Transform, integrating projections across lines, the MSIRT uses arbitrary given curves, which are derived from primitives contours. MSIRT leads to peaks once similar shapes are met in the projected image. For seek of genericity and invariance with respect to geometric transformations, we consider different primitives derived from MPEG7 dataset. Each object undergoes a series of preprocessing steps, segmentation and contour extraction, for generating the corresponding primitive. For each query object, the MSIRT is applied with respect to the different primitives and a vote approach will be used for object recognition. Validation of the proposed approach is done on the MPEG7 dataset, giving an accuracy of 94%. Comparison with some known approaches demonstrates the effectiveness of the proposed approach in detecting complex objects, even under geometric transformations.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Raghavender Rao, Y., Prathapani, N., Nagabhooshanam, E.: Application of normalized cross correlation to image registration. Int. J. Res. Eng. Technol. 05(3), 12–16 (2014)
Hasegawa, M., Tabbone, S.: Amplitude-only log radon transform for geometric invariant shape descriptor. Pattern Recogn. 47(2), 643–658 (2014). doi:10.1016/j.patcog.2013.07.024. Elsevier
Tabbone, S., Wendling, L., Salmon, J.-P.: A new shape descriptor defined on the radon transform. Comput. Vis. Image Understand. 102(1), 42–51 (2006). doi:10.1016/j.cviu.2005.06.005. Elsevier
Rojbani, H., Elouedi, I., Hamouda, A.: R\(\theta \)-signature: a new signature based on radon transform and its application in buildings extraction. In: IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), pp. 490–495. IEEE (2011)
Hasegawa, M., Tabbone, S.: Histogram of radon transform with angle correlation matrix for distortion invariant shape descriptor. Neurocomputing 173, 24–35 (2016). doi:10.1016/j.neucom.2015.04.100. Elsevier
Hasegawa, M., Tabbone, S.: A shape descriptor combining logarithmic scale histogram of radon transform and phase-only correlation function. In: International Conference on Document Analysis and Recognition (ICDAR), pp. 182–186. IEEE (2011)
Ines, E., Dhikra, H., Regis, F., Amine, N.-A., Atef, H.: Fingerprint recognition using polynomial discrete radon transform. In: 4th International Conference on Image Processing Theory, Tools and Applications (IPTA), pp. 1–6. IEEE (2014)
Hendriks, C.L.L., Van Ginkel, M., Verbeek, P.W., Van Vliet, L.J.: The generalized radon transform: sampling, accuracy and memory considerations. Pattern Recogn. 38(12), 2494–2505 (2005). doi:10.1016/j.patcog.2005.04.018. Elsevier
Elouedi, I., Fournier, R., Nait-Ali, A., Hamouda, A.: Generalized multidirectional discrete radon transform. Sign. Process. 93(1), 345–355 (2013). doi:10.1016/j.sigpro.2012.07.031. Elsevier
de Oliveira, A.B., da Silva, P.R., Barone, D.A.C.: A novel 2d shape signature method based on complex network spectrum. Pattern Recogn. Lett. 63, 43–49 (2015). doi:10.1016/j.patrec.2015.05.018. Elsevier
Latecki, L.J., Lakamper, R., Eckhardt, T.: Shape descriptors for non-rigid shapes with a single closed contour. In: IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 424–429. IEEE (2000)
Beylkin, G.: Discrete Radon transform. IEEE Trans. Acoustics Speech Sign. Process. 35(2), 162–172 (1987)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Hammouda, G., Hammouda, A., Sellami, D. (2018). Complex Object Recognition Based on Multi-shape Invariant Radon Transform. In: Czarnowski, I., Howlett, R., Jain, L. (eds) Intelligent Decision Technologies 2017. IDT 2017. Smart Innovation, Systems and Technologies, vol 73. Springer, Cham. https://doi.org/10.1007/978-3-319-59424-8_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-59424-8_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-59423-1
Online ISBN: 978-3-319-59424-8
eBook Packages: EngineeringEngineering (R0)