Majority Ordering and the Morphological Pattern Spectrum

Binary and grayscale mathematical morphology have many applications in different area. On the other hand, colour morphology is not widespread. The reason is the lack of a unique ordering of colour that makes the extension of grayscale morphology to colour images not straightforward. We will introduce a new majority sorting scheme that can be applied on binary, grayscale and colour images. It is based on the area of each colour or grayscale present in the image, and has the advantage of being independent of the values of the colours or grayvalues. We will take a closer look at the morphological pattern spectrum and will show the possible differences of the morphological pattern spectrum on colour images with the grayscale image pattern spectrum.

[1]  Sujata Banerjee,et al.  C-factor: A morphological shape descriptor , 2005, Journal of Mathematical Imaging and Vision.

[2]  Emanuele Trucco,et al.  Computer and Robot Vision , 1995 .

[3]  Allan Hanbury,et al.  Mathematical Morphology in the HLS Colour Space , 2001, BMVC.

[4]  Linda G. Shapiro,et al.  Computer and Robot Vision , 1991 .

[5]  Jean Serra,et al.  Image Analysis and Mathematical Morphology , 1983 .

[6]  Petros Maragos,et al.  Pattern Spectrum and Multiscale Shape Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  M. Handzic 5 , 1824, The Banality of Heidegger.

[8]  Richard Alan Peters,et al.  Mathematical morphology for angle-valued images , 1997, Electronic Imaging.

[9]  B. S. Manjunath,et al.  Peer group filtering and perceptual color image quantization , 1999, ISCAS'99. Proceedings of the 1999 IEEE International Symposium on Circuits and Systems VLSI (Cat. No.99CH36349).