Geometric Shape Characterisation Based on a Multi-Sweeping Paradigm

The characterisation of geometric shapes produces their concise description and is, therefore, important for subsequent analyses, example in Computer Vision, Machine Learning, or shape matching. A new method extracting vectors 2D is proposed this paper. interest, embedded into a raster space, swept several times by sweep-lines having different slopes. interior shape’s points, being the middle its boundary laying on actual sweep-line, are identified at each stage sweeping process. midpoints then connected iteratively chains. chains filtered, vectorised, normalised. obtained polylines from vectorisation step used to design vector further application-specific analyses. was verified numerous shapes, where single- multi-threaded implementations were compared. Finally, vectors, among which some rotated scaled, determined these shapes. demonstrated good rotation- scaling-invariant identification equal