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. While x-ray imaging has the potential to detect pits, traditional commercially available equipment is expensive and bulky, and implementation on the processing line is cumbersome. An x-ray inspection system using an array of photodiode based x-ray detectors in a linescan configuration whose outputs are combined to produce a one dimensional signal would be simpler, faster, and more economical. The data collection process is then reduced from a two dimensional image to a much simpler one dimensional signal, resulting in faster and simpler processing and classification. An algorithm designed to differentiate unpitted from pitted cherries for such a system yielded recognitiothe unpitted cherries, with a total error rate of 3.5%. When the a of pitted fruit, 100% of pitted cherries were detected with a orientation is controlled after pitting, total error is reduced to 1%.
[1]
P. H. Southwell,et al.
Engineering in Agriculture
,
1942,
Nature.
[2]
S. Edward Law.
SCATTER OF NEAR‐INFRARED RADIATION BY CHERRIES AS A MEANS OF PIT DETECTION
,
1973
.
[3]
E. J. Timm,et al.
Potential Methods for Detecting Pits in Tart Cherries
,
1991
.
[4]
Pictiaw Chen,et al.
Real-Time Detection of Pits in Processed Cherries by Magnetic Resonance Projections
,
1994
.
[5]
R. P. Haff,et al.
NEW METHOD FOR BATCH TESTING of RED TART CHERRIES FOR the PRESENCE of PITS
,
1994
.
[6]
C. J. Clark,et al.
Application of magnetic resonance imaging to pre- and post-harvest studies of fruits and vegetables
,
1997
.
[7]
Pictiaw Chen,et al.
Detection of pits in olives under motion by nuclear magnetic resonance
,
1997
.
[8]
Thomas F. Schatzki,et al.
Method for batch testing red tart cherries for the presence of pit fragments
,
1999
.
[9]
T. C. Pearson,et al.
Non-Destructive Detection of Pits in Dried Plums
,
2005
.