Real-time Detection of Foreign Substance in Seaweed using Pushbroom Hyperspectral Imaging

Abstract

Foreign substances in food cause disgust to consumers and some cases directly harm their health. Therefore, the detection of foreign substances in the food production process is very important, and active research has been conducted to date. In the case of the RGB image-based foreign substance detection system currently used in industrial sites, the accuracy is low when detecting foreign substances that are difficult to distinguish in the visible spectrum. Besides, it is difficult to detect foreign substances having similar color and texture to seaweed. In this paper, we propose a method for detecting foreign substances in seaweed using VNIR (Visible and Near-Infrared) hyperspectral images. The VNIR hyperspectral image is characterized by dividing the wavelength from the visible spectrum to the near-infrared spectrum very finely, and the camera used in the experiment has a total of 224 spectral characteristics per pixel. Spectral analysis of the acquired hyperspectral image enables more sophisticated foreign substance detection than the conventional method, and the advantage is that accurate location information and shape information can be obtained through pixel-based detection. Through the experiment, it has proven that it is possible to detect foreign substances that are difficult to distinguish with the naked eye, such as foreign substances having a similar color as seaweed or very small (about 1mm) foreign substances. © 2020 IEEE.