X-ray imaging checks cherry pits

Sept. 24, 2009
SEPTEMBER 24, 2009--A simpler, faster, and more economical x-ray inspection system has been developed to check for cherry pits by modifying a traditional x-ray detector.

SEPTEMBER 24, 2009--X-ray imaging has been used to detect cherry pits, but the traditional equipment is both expensive and bulky, and implementation on the processing line is cumbersome. A simpler, faster, and more economical x-ray inspection system has been developed by modifying a traditional x-ray detector.

The presence of pits in processed cherries is a concern for both processors and consumers, in many cases causing injury and potential lawsuits. While machines used for pitting cherries are extremely efficient, if one or more plungers in a pitting head become misaligned, a large number of pits may pass before corrective action is taken, and consequently the overall pit count is generally much higher.

The new system was developed by agricultural engineer Ronald Haff and his colleagues at WRRC Imaging and Sorting Lab, a research group within the US Department of Agriculture, Agricultural Research Service, Plant Mycotoxin Research Unit, at the Western Regional Research Center in Albany, CA.

The new system has reduced the data collection process from a 2D image to a much simpler 1 dimensional signal, which results in faster and simpler processing and classification of the resulting signal than conventional imaging and processing. This simplification reduces the size and complexity of the x-ray detection system significantly, leading to lower cost and greater ease of implementation.

An algorithm designed to differentiate unpitted from pitted cherries yielded recognition rates of 97.3% for the pitted and 94% for the unpitted cherries, with a total error rate of 3.5%. When the algorithm was adjusted to maximize removal of pitted fruit, 100% of pitted cherries were detected with a total error rate of 8.5%. If orientation could be controlled after pitting, total error could be as low as 1%.

For more information, go to: http://www.ars.usda.gov/research/publications/publications.htm?seq_no_115=240157

-- Posted by Conard Holton, Vision Systems Design, www.vision-systems.com

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