Abstract
The Geometric Hashing technique was introduced about a decade ago, as an efficient method for object recognition in computer vision. Since then, it has been applied in many other fields. The underlying idea of Geometric Hashing is using a database for storing pieces of information of known geometric objects, in such a way that allows fast recognition of an unknown query object. The main advantage of this technique is its ability to perform partial matching between geometric objects, for example, for recognizing objects in an image that are partially occluded or have undergone some transformation. It does not depend on the existence of any particular predefined features in the matched objects. It is usually very easy to implement, and it performs fast and accurately. The Geometric Hashing technique is an indexing-based approach, where local features of objects are encoded and stored in a database. Such approaches are now widely recognized as the method of choice for implementing reliable recognition systems that handle large model databases.
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