{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/101334"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/101334","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Methods for recognizing patterns in digitized line drawings","abstract":"A system for the extraction and storage of line and region data from digitized engineering line drawings, first proposed by Watson et.al.[3] and further developed by Bixler et.al.[4], is completed. As a means for the automatic analysis of picture content, a model based recognizer for line patterns is developed. The pattern matcher uses a simple scheme to decompose a line drawing into basic parts: strokes and junctions, and then finds graph isomorphisms between known line pattern models stored in a database and portions of the image line data. Hu's moment invariants [16] are used to match simple shapes and prune the search space. Information about the connectivity of patterns matched in the image is retained, allowing higher level analysis of image content. A second method for calculating a moment signature from line data is presented. This method makes use of a spline approximation of the line data and Legendre polynomials. Some methods for recognizing incomplete line patterns and partially occluded curves are also discussed, and some experiments are performed.","abstract_html":"A system for the extraction and storage of line and region data from digitized engineering line drawings, first proposed by Watson et.al.[3] and further developed by Bixler et.al.[4], is completed. As a means for the automatic analysis of picture content, a model based recognizer for line patterns is developed. The pattern matcher uses a simple scheme to decompose a line drawing into basic parts: strokes and junctions, and then finds graph isomorphisms between known line pattern models stored in a database and portions of the image line data. Hu&#x27;s moment invariants [16] are used to match simple shapes and prune the search space. Information about the connectivity of patterns matched in the image is retained, allowing higher level analysis of image content. A second method for calculating a moment signature from line data is presented. This method makes use of a spline approximation of the line data and Legendre polynomials. 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As a means for the automatic analysis of picture content, a model based recognizer for line patterns is developed. The pattern matcher uses a simple scheme to decompose a line drawing into basic parts: strokes and junctions, and then finds graph isomorphisms between known line pattern models stored in a database and portions of the image line data. Hu's moment invariants [16] are used to match simple shapes and prune the search space. Information about the connectivity of patterns matched in the image is retained, allowing higher level analysis of image content. A second method for calculating a moment signature from line data is presented. This method makes use of a spline approximation of the line data and Legendre polynomials. 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