Abstract
In this paper we apply cellular neural networks for color image segmentation. Color aerial photographs will be analyzed. Two types of color models: RGB and HSV will be taken into account and compared. In resulting images we will distinguish some objects like houses, roads, trees and others. The selection of the objects will be based on the color value. We show that the choice of color model influences the results.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Aizenberg, I., Aizenberg, N., Hiltner, J., Moraga, C., Zu Bexten, E.M.: Cellular neural networks and computational intelligence in medical image processing. Image and Vision Computing 19(4), 177–183 (2001)
Arena, P., Basile, A., Bucolo, M., Fortuna, L.: Image processing for medical diagnosis using CNN. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 497(1), 174–178 (2003)
Bertucco, L., Coltelli, M., Nunnari, G., Occhipinti, L.: Cellular neural networks for real-time monitoring of volcanic activity. Computers & Geosciences 25(2), 101–117 (1999)
Cheng, H.D., Jiang, X.H., Sun, Y., Wang, J.: Color image segmentation: advances and prospects. Pattern Recognition 34(12), 2259–2281 (2001)
Chua, L.O., Yang, L.: Cellular neural networks: Theory. IEEE Transaction on Circuits and Systems 35, 1257–1272 (1988)
Chua, L.O., Yang, L.: Cellular neural networks: Applications. IEEE Transaction on Circuits and Systems 35, 1273–1290 (1988)
Egmont-Petersen, M., de Ridder, D., Handels, H.: Image processing with neural networks — a review. Pattern Recognition 35(10), 2279–2301 (2002)
Gaobo, Y., Zhaoyang, Z.: Video object segmentation for head—shoulder sequences in the cellular neural networks architecture. Real-Time Imaging 9(3), 171–178 (2003)
Harrer, H., Nossek, J.A.: Discrete-time Cellular Neural Networks. International Journal of Circuit Theory and Applications 20(5), 453–467 (1992)
Kacprzak, T., Ślot, K.: Sieci neuronowe komórkowe. Wyd. Naukowe PWN (1995) (in Polish)
Kosiński, R.A.: Sztuczne sieci neuronowe. WNT (2002) (in Polish)
Kurugollu, F., Sankur, B., Harmanci, A.E.: Image segmentation by relaxation using constraint satisfaction neural network. Image and Vision Computing 20(7), 483–497 (2002)
Milanova, M., Büker, U.: Object recognition in image sequences with cellular neural networks. Neurocomputing 31(1), 125–141 (2000)
Milanova, M., Almeida, P.E.M., Okamoto Jr., J., Godoy Simöes, M.: Applications of cellular neural networks for shape from shading problem. LNCS (LNAI), pp. 52–63. Springer, Heidelberg (1999)
Slavova, A.: Applications of some mathematical methods in the analysis of cellular neural networks. Journal of Computational and Applied Mathematics 114(2), 387–404 (2000)
Vilarino, D.L., Brea, V.M., Cabello, D., Pardo, J.M.: Discrete-time CNN for image segmentation by active contours. Pattern Recognition Letters 19(8), 721–734 (1998)
Vilarino, D.L., Cabello, D., Pardo, J.M., Brea, V.M.: Cellular neural networks and active contours: a tool for image segmentation. Image and Vision Computing 21(2), 189–204 (2003)
Wang, L., de Gyvez, J.P., Sánchez-Sinencio, E.: Time Multiplexed Color Image Processing Based on a CNN with Cell-State Outputs. IEEE Transactions on very large csale Integration (VLSI) Systems 6(2) (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wilbik, A. (2005). Cellular Neural Networks for Color Image Segmentation. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Biological Inspirations – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550822_82
Download citation
DOI: https://doi.org/10.1007/11550822_82
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28752-0
Online ISBN: 978-3-540-28754-4
eBook Packages: Computer ScienceComputer Science (R0)