Abstract
In this paper, we present a new color image segmentation algorithm which is based on fuzzy mathematical morphology. After a color pixel projection into an attribute space, segmentation consists of detecting the different modes associated with homogeneous regions. In order to detect these modes, we show how a color image can be viewed as a fuzzy set with its associated membership function corresponding to a mode which is defined by a color cooccurrence matrix and by mode concavity properties. A new developed fuzzy morphological transformation is then applied to this membership function in order to identify the modes. The performance of our proposed fuzzy morphological approach is then presented using a test color image, and is then compared to the competitive learning algorithm.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
BLOCH I. and MAITRE H. (1995): Fuzzy mathematical morphologies: A comparative study. Pattern Recognition, 9 (28):1341–1387.
PARK S.H, YUN I.D, and, LEE S.U. (1998): Color image segmentation based on 3-D clustering: morphological approach. Pattern Recognition, 31(8):1061–1076.
POSTAIRE J.-G. and VASSEUR C. (1980): A convexity testing method for cluster analysis. I.E.E.E. Transactions on Systems and Man Cybernetics, 10:145–149.
TREMEAU A., COLANTONI P. and LAGET B. (1996): On color segmentation guided by the cooccurrence matrix. OSA Annual conference on Optics and Imaging in the Information Age, 30–38.
TURPIN-DHILLY S. and BOTTE-LECOCQ C. (1998): Application of fuzzy mathematical morphology for pattern classification. Advances in Data Science and Classification, Proceeding of the 6th Conference of IFCS’98, 125–130.
UCHIYAMA T. AND ARBIB M. A. (1994): Color image segmentation using competitive learning. I.E.E.E. Transactions on Pattern Analysis and Machine Intelligence, 16(12):1197–1206.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin · Heidelberg
About this paper
Cite this paper
Gillet, A., Botte-Lecocq, C., Macaire, L., Postaire, JG. (2000). Application of Fuzzy Mathematical Morphology for Unsupervised Color Pixels Classification. In: Kiers, H.A.L., Rasson, JP., Groenen, P.J.F., Schader, M. (eds) Data Analysis, Classification, and Related Methods. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-59789-3_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-59789-3_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67521-1
Online ISBN: 978-3-642-59789-3
eBook Packages: Springer Book Archive