Abstract
An original “main stem” concept for image matching is presented. The main stem is a global image feature defined as a tree of reduced components without redundant and noise components. It has been shown that this image feature is strongly invariant to different types of topological transformations and contains useful information about “meaningful” image regions and their interrelations. We present how to construct the main stem and we devise an appropriate method for image matching that is based on their stems. The method for mapping the main stem onto a feature vector and appropriate metric to compare between the feature vectors in the selected representation space are presented. Preliminary experiments show the validity of the proposed method for robust image matching.
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.
