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Proceedings Paper

Detection and segmentation of multiple touching product inspection items
Author(s): David P. Casasent; Ashit Talukder; Westley Cox; Hsuan-Ting Chang; David Weber
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Paper Abstract

X-ray images of pistachio nuts on conveyor trays for product inspection are considered. The first step in such a processor is to locate each individual item and place it in a separate file for input to a classifier to determine the quality of each nut. This paper considers new techniques to: detect each item (each nut can be in any orientation, we employ new rotation-invariant filters to locate each item independent of its orientation), produce separate image files for each item [a new blob coloring algorithm provides this for isolated (non-touching) input items], segmentation to provide separate image files for touching or overlapping input items (we use a morphological watershed transform to achieve this), and morphological processing to remove the shell and produce an image of only the nutmeat. Each of these operations and algorithms are detailed and quantitative data for each are presented for the x-ray image nut inspection problem noted. These techniques are of general use in many different product inspection problems in agriculture and other areas.

Paper Details

Date Published: 18 December 1996
PDF: 12 pages
Proc. SPIE 2907, Optics in Agriculture, Forestry, and Biological Processing II, (18 December 1996); doi: 10.1117/12.262860
Show Author Affiliations
David P. Casasent, Carnegie Mellon Univ. (United States)
Ashit Talukder, Carnegie Mellon Univ. (United States)
Westley Cox, Carnegie Mellon Univ. (United States)
Hsuan-Ting Chang, National Chung Cheng Univ. (Taiwan)
David Weber, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 2907:
Optics in Agriculture, Forestry, and Biological Processing II
George E. Meyer; James A. DeShazer, Editor(s)

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