Abstract
Geometric hashing is a model-based object recognition technique for detecting objects which can be partially overlapping or partly occluded. In its simplest form, the geometric hashing method assumes relatively noise-free data and is applied to objects with points as local features. However, extracting of the locations of point features is inherently error-prone. Line features, compared with point features, can generally be extracted with greater accuracy. The application of line features for geometric hashing to the recognition of two-dimensional (2D) (or flat 3D) objects undergoing various geometric transformations is investigated.
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