Abstract
Multivariate mathematical morphology is increasing becoming a powerful utility for color image processing and analysis. In the paper, a new vector ordering scheme based on distances in the HSI color space is proposed. The methodology first uses nonlinear weighted combination with color distances, where vectors are reduced to scalars with the help of weighted coefficients. These coefficients are entirely determined by the saturation-intensity plane, which fit in with human perception. Then a lexicographical cascade is employed to complete total ordering. On the basis of the ordering approach, new erosion and dilation operations are defined. The performance of proposed is illustrated by means of color edge detection. Experimental results demonstrate its advantageous effectiveness. Additionally, the proposed framework can be also extended for other perceptual color representations based on polar coordinate.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
