Detection and segmentation of multiple touching product inspection items

David P. Casasent; Ashit Talukder; Westley Cox; Hsuan-Ting Chang; David Weber

doi:10.1117/12.262860

18 December 1996 Detection and segmentation of multiple touching product inspection items

David P. Casasent, Ashit Talukder, Westley Cox, Hsuan-Ting Chang, David Weber

Proceedings Volume 2907, Optics in Agriculture, Forestry, and Biological Processing II; (1996) https://doi.org/10.1117/12.262860
Event: Photonics East '96, 1996, Boston, MA, United States

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.

Citation Download Citation

David P. Casasent, Ashit Talukder, Westley Cox, Hsuan-Ting Chang, and David Weber "Detection and segmentation of multiple touching product inspection items", Proc. SPIE 2907, Optics in Agriculture, Forestry, and Biological Processing II, (18 December 1996); https://doi.org/10.1117/12.262860

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