X-ray agricultural product inspection: segmentation and classification

David P. Casasent; Ashit Talukder; Ha-Woon Lee

doi:10.1117/12.285589

18 September 1997 X-ray agricultural product inspection: segmentation and classification

David P. Casasent, Ashit Talukder, Ha-Woon Lee

Proceedings Volume 3205, Machine Vision Applications, Architectures, and Systems Integration VI; (1997) https://doi.org/10.1117/12.285589
Event: Intelligent Systems and Advanced Manufacturing, 1997, Pittsburgh, PA, United States

Abstract

Processing of real-time x-ray images of randomly oriented and touching pistachio nuts for product inspection is considered. We describe the image processing used to isolate individual nuts (segmentation). This involves a new watershed transform algorithm. Segmentation results on approximately 3000 x-ray (film) and real time x-ray (linescan) nut images were excellent (greater than 99.9% correct). Initial classification results on film images are presented that indicate that the percentage of infested nuts can be reduced to 1.6% of the crop with only 2% of the good nuts rejected; this performance is much better than present manual methods and other automated classifiers have achieved.

Citation Download Citation

David P. Casasent, Ashit Talukder, and Ha-Woon Lee "X-ray agricultural product inspection: segmentation and classification", Proc. SPIE 3205, Machine Vision Applications, Architectures, and Systems Integration VI, (18 September 1997); https://doi.org/10.1117/12.285589

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