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.

Two-color mixing for classifying agricultural products for safety and quality.

We show that the chromaticness of the visual signal that results from the two-color mixing achieved through an optically enhanced binocular device is directly related to the band ratio of light intensity at the two selected wavebands. A technique that implements the band-ratio criterion in a visual device by using two-color mixing is presented here. The device will allow inspectors to identify targets visually in accordance with a two-wavelength band ratio. It is a method of inspection by human vision assisted by an optical device, which offers greater flexibility and better cost savings than a multispectral machine vision system that implements the band-ratio criterion. With proper selection of the two narrow wavebands, discrimination by chromaticness that is directly related to the band ratio can work well. An example application of this technique for the inspection of carcasses chickens of afficted with various diseases is given. An optimal pair of wavelengths of 454 and 578 nm was selected to optimize differences in saturation and hue in CIE LUV color space among different types of target. Another example application, for the detection of chilling injury in cucumbers, is given, here the selected wavelength pair was 504 and 652 nm. The novel two-color mixing technique for visual inspection can be included in visual devices for various applications, ranging from target detection to food safety inspection.

Two-wave-band color-mixing binoculars for the detection of wholesome and unwholesome chicken carcasses: a simulation.

Visual inspection of wholesome and unwholesome chicken carcasses with a novel two-narrowband color-mixing technique for optically enhanced binoculars is simulated. From mean spectra of wholesome, airsacculitis (air-sac), cadaver, inflammatory process (IP), septicemia-toxemia (septox), and tumor chicken samples, 10 nm wave-band pairs are selected using color difference and chromaticness difference indices for simulation of multitarget and single-target detection. The color appearance simulation uses the CIECAM97s color appearance model. Results show that for multitarget detection, the wave-band pair of (454 nm, 578 nm) is able to differentiate all six chicken conditions. For single-target detection of wholesome, air-sac, cadaver, and tumor, the wave-band pairs of (449 nm, 571 nm), (441 nm, 576 nm), (458 nm, 576 nm), and (431 nm, 501 nm), respectively, easily distinguish the target condition from the other five conditions. For single-target detection of IP and septox, the wave-band pairs of (454 nm, 591 nm) and (454 nm, 590 nm), respectively, are able to differentiate the target conditions from wholesome and tumor conditions but have difficulty with the other chicken conditions. The two-color-mixing technique shows promise for use in small-scale processing plant environments to improve the visual inspection process.