Three-color mixing for classifying agricultural products for safety and quality.
A three-color mixing application for food safety inspection is presented. It is shown that the chromaticness of the visual signal resulting from the three-color mixing achieved through our device is directly related to the three-band ratio of light intensity at three selected wavebands. An optical visual device using three-color mixing to implement the three-band ratio criterion is presented. Inspection through human vision assisted by an optical device that implements the three-band ratio criterion would offer flexibility and significant cost savings as compared to inspection with a multispectral machine vision system that implements the same criterion. Example applications of this optical three-color mixing technique are given for the inspection of chicken carcasses with various diseases and for apples with fecal contamination. With proper selection of the three narrow wavebands, discrimination by chromaticness that has a direct relation with the three-band ratio can work very well. In particular, compared with the previously presented two-color mixing application, the conditions of chicken carcasses were more easily identified using the three-color mixing application. The novel three-color mixing technique for visual inspection can be implemented on visual devices for a variety of applications, ranging from target detection to food safety inspection.
Ding
Fujian
F
Instrumentation and Sensing Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, ARS, USDA, MD 20705, USA.
Chen
Yud-Ren
YR
Chao
Kuanglin
K
Kim
Moon S
MS
D000383:Agriculture / Q000295:instrumentation* / Q000379:methods; D000465:Algorithms; D003124:Colorimetry / Q000295:instrumentation*; D003257:Consumer Product Safety; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005504:Food Analysis / Q000295:instrumentation / Q000379:methods; D005506:Food Contamination / Q000032:analysis; D007089:Image Enhancement / Q000295:instrumentation* / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D055096:Optical Devices; D011786:Quality Control