Optimization of illuminant spectrum for visual detection of foreign substances in jams

Abstract

Carrying out accurate visual inspection to remove the foreign substances is a crucial issue in food industry. Also in jam factories, the visual inspection by inspectors has been strengthened. However, it is difficult to remove the foreign substances perfectly because they are stained with fruit juice and their color becomes similar to the jam. To overcome the problem, we have proposed the functional illuminant that emphasizes the color difference between jams and foreign substances for the visual inspection. Our previous method for developing the functional illuminant is time consuming to design spectrum. Moreover, this method has low flexibility because it designs an illuminant whose spectrum is produced by a combination of only three types of LEDs, and it has a constraint that the color of the illuminant must be specified before designing. In this study, we propose a new method that formulates the design procedure as an optimization problem solved by NLP (nonlinear programming). The proposed method can combine more than three types of LEDs. Furthermore, our method does not require a constraint for the color of the illuminant. As a result, the color difference by the functional illuminant designed by the proposed method is bigger than the previous method.