Skip to main content
ARS Home » Midwest Area » East Lansing, Michigan » Sugarbeet and Bean Research » Research » Publications at this Location » Publication #241764
Title: Hyperspectral Imaging for Defect Detection of Pickling Cucumber

Author
item ARIANA, DIWAN - Michigan State University
item Lu, Renfu

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 9/20/2009
Publication Date: 5/1/2010
Citation: Ariana, D., Lu, R. 2010. Hyperspectral Imaging for Defect Detection of Pickling Cucumber. In: Sun, Da-Wen, editor. Hyperspectral Imaging for Food Quality Analysis and Control. Boston, MA: Elsevier Inc. p. 431-437.

Interpretive Summary:

Technical Abstract: This book chapter reviews the recent progress on hyperspectral imaging technology for defect inspection of pickling cucumbers. The chapter first describes near-infrared hyperspectral reflectance imaging technique for the detection of bruises on pickling cucumbers. The technique showed good detection accuracies (>90%) for bruises on the pickling cucumbers. The chapter then reviews a hyperspectral imaging system that operates in both reflectance and transmittance modes for acquiring reflectance images in the visible range (400-750 nm) and transmittance images in the near-infrared region (750-1000 nm). This special design feature enables detection of both surface characteristics (such as color) and internal defect (hollow or split center) of pickling cucumbers. Algorithms for detecting internal defect in cucumbers are briefly described. The system achieved good defect detection accuracy. The chapter ends with some concluding remarks on hyperspectral imaging for sorting and grading pickling cucumbers and pickled products for both external and internal defect.