Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Efficiently Computable Metric for Comparing Polygonal Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Similar shape retrieval using a structural feature index
Information Systems
Visual Image Retrieval by Elastic Matching of User Sketches
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature-index-based similar shape retrieval
Proceedings of the third IFIP WG2.6 working conference on Visual database systems 3 (VDB-3)
Handbook of discrete and computational geometry
Handbook of discrete and computational geometry
Relaxing the Triangle Inequality in Pattern Matching
International Journal of Computer Vision
A Multistep Approach for Shape Similarity Search in Image Databases
IEEE Transactions on Knowledge and Data Engineering
Parametric correspondence and chamfer matching: two new techniques for image matching
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
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We consider the problem of finding the best match for a given query shape among candidate shapes stored in a shape base. This is central to a wide range of applications, such as, digital libraries, digital film databases, environmental sciences, and satellite image repositories. We present an efficient matching algorithm built around a novel similarity criterion and based on shape normalization about the shape's diameter, which reduces the effects of noise or limited accuracy during the shape extraction procedure. Our matching algorithm works by gradually "fattening" the query shape untilthe best match is discovered. The algorithm exhibits poly-logarithmic time behavior assuming uniform distribution of the shape vertices in the locus of their normalized positions.