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Proceedings Paper

Model-based flaw detection and classification in web materials
Author(s): Dragana P. Brzakovic; Hamed Sari-Sarraf; Milorad Neskovic
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Paper Abstract

This paper describes the design and implementation of an inspection system that detects and classifies flaws in uniform web materials. The first part of this paper describes a general procedure for designing such an inspection system. The second part concentrates on a case study and details the specific algorithms and results. The overall inspection system design incorporates five subsystems: sensing, flaw detection, flaw characterization, feature analysis, and classification. The case study involves flaws consisting of bloblike structural elements; a specific spatial arrangement of the blobs is the major characteristics of the flaw class under study. The emphasis of the paper is on the recognition of the flaws independently of their position, orientation and size. The study incorporates analysis on synthetically generated flaws as well as the ones acquired on the production line.

Paper Details

Date Published: 10 June 1994
PDF: 12 pages
Proc. SPIE 2232, Signal Processing, Sensor Fusion, and Target Recognition III, (10 June 1994); doi: 10.1117/12.177742
Show Author Affiliations
Dragana P. Brzakovic, Lehigh Univ. (United States)
Hamed Sari-Sarraf, Oak Ridge National Lab. (United States)
Milorad Neskovic, Lehigh Univ. (United States)

Published in SPIE Proceedings Vol. 2232:
Signal Processing, Sensor Fusion, and Target Recognition III
Ivan Kadar; Vibeke Libby, Editor(s)

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