| Abstract: | Residual bran on milled rice is directly related to its quality. This study proposes a method to measure the residual bran patterns on a single rice grain by using hyperspectral imaging (HSI). HSI is a sensing technique that combines both spatial and spectral information and may be used for chemical compound identification and quantification. In this study, HSI was applied to assess rice bran residue nondestructively. In the experiment, rice samples were milled and scanned with an HSI system. Afterward, the rice samples were dyed to enable the residual bran to be identified with optical microscopy and image processing algorithms. Classifiers were then developed to predict the rice bran residue by using the HSI measurements as inputs. The predicted images were compared with the micrograph images for classifier performance evaluation. The proposed approach can estimate the residual bran distribution on milled rice surface with an accuracy of 93.5%. |
