NeTra: a toolbox for navigating large image databases
Multimedia Systems - Special issue on video content based retrieval
Area operators for edge detection
Pattern Recognition Letters
Edge-based structural features for content-based image retrieval
Pattern Recognition Letters - Special issue on image/video indexing and retrieval
CAIVL '97 Proceedings of the 1997 Workshop on Content-Based Access of Image and Video Libraries (CBAIVL '97)
An RCE-based Associative Memory with Application to Human Face Recognition
Neural Processing Letters
Segmentation of Complex Images Based on Component-Trees: Methodological Tools
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
Component-Trees and Multi-value Images: A Comparative Study
ISMM '09 Proceedings of the 9th International Symposium on Mathematical Morphology and Its Application to Signal and Image Processing
A document binarization method based on connected operators
Pattern Recognition Letters
Interactive segmentation based on component-trees
Pattern Recognition
Component-Trees and Multivalued Images: Structural Properties
Journal of Mathematical Imaging and Vision
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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.