Abstract
Mathematical morphology is a nonlinear filtering method that can be used in noise suppression, feature extraction, edge detection, image segmentation and other image processing problems. Thanks to the powerful ability of matrix computation provided by the OSSC (Open-source Software for Scientific Computation), we can establish a professional mathematical morphology toolbox. During the past years, our team has dedicated to a mathematical morphology toolbox on Scilab called SciMM toolbox. In this paper, we focus on the latest progress of SciMM. A new image segmentation function based on watershed transform is added to SciMM, which is coded with C as a dynamic link library that can be called by Scilab script through the interface function. The toolbox's folder hierarchy is then re-organized according to the newest guideline of making a Scilab toolbox. Some functions are improved for better efficiency, esting results.
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.
