Non-destructive Detection of Damaged Raw Unhulled Grains Using Image Processing -Detection of Damaged Grains by Stinkbugs-

概要

論文の詳細を見る
The purpose of this study is to detect damaged rice grains, which are unhulled and internally damaged by stinkbugs, using an image processing system. The experimental apparatus mainly consists of a multi-spectral camera, fiber-optic light sources, plane-emission light sources, sample plate and personal computer. More specifically, the transmitted light images of 50 grains on the sample plate were generated when the grains were illuminated from the back of the sample plate. Furthermore, while the sample plate was fixed, the light sources were changed over to the fiber-optic light sources irradiating the grains equally from four corners on the upper side of the sample plate. In succession, the raw grains were hulled and visually confirmed to see if any damage had been caused by stinkbugs. The images were processed in the methods using binary conversion processing, contraction processing and mask operation. In this regard, the mean gray level of each normal grain and the number of pixels within the damaged parts of grains were obtained to draw a scatter chart from which the linear discriminant function was derived. As a result, the undamaged grains and stinkbug-damaged grains were discriminated from each other. It was found that the total discrimination rate was 94.6 percent. In conclusion, the possibility of detecting stinkbug-damaged grains using raw unhulled grains can be suggested when the image processing algorithm constructed during this research comes into use.

Non-destructive Detection of Damaged Raw Unhulled Grains Using Image Processing -Detection of Damaged Grains by Stinkbugs-

スポンサーリンク

概要

著者

関連論文

スポンサーリンク