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Proceedings Paper

Aspects in automatic nesting of irregular shapes
Author(s): Khoi Hoang
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Paper Abstract

Nesting of shoe parts onto a leather hide is a very complex puzzle. This is because firstly, both the shoe parts and the leather hide are of irregular shapes and secondly, leather quality is not uniform throughout the hide, certain zones are only suitable for certain types of shoe parts. Moreover, leather hide bears stretch directions which some shoe parts are not permitted to be nested in at certain angles to the hide's stretch directions. Thirdly, the pose of defects in some shoe parts can be acceptable or unacceptable depending on the manufacturer's quality standard. Machine vision researchers have been attempting to capture the hide defect map and use this data file for assisting the computerization nesting of the irregular shapes. There are many challenging tasks in the visual inspection stage which affect the performance of the nesting systems. An essential assignment is the clustering of leather defects. Two vital parameters required in the clustering of defects are the minimum Euclidean distance between defects to be clustered and the re-classification of the newly formed cluster if it contains more than one type of defect or satisfied more serious defect type definition. In order to minimize the wastage in yield, this work recommends that during the inspection stage, only defects of the same type are to be clustered and the process should cease at the point where the newly formed cluster is to become a more serious defect type. The question of minimum Euclidean distance should be considered at both inspection stage as a preliminary clustering operation and at the nesting stage when the shoe size and part shapes are known, as a fine tuned process.

Paper Details

Date Published: 3 October 1995
PDF: 8 pages
Proc. SPIE 2588, Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling, (3 October 1995); doi: 10.1117/12.222674
Show Author Affiliations
Khoi Hoang, The Univ. of New South Wales (Australia)


Published in SPIE Proceedings Vol. 2588:
Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling
David P. Casasent, Editor(s)

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