Low-density foreign body detection in food products using single-shot grid-based dark-field X-ray imaging

Abstract

This study presents a novel approach for detecting low-density foreign bodies (FBs) in food products using single-shot grid-based dark-field X-ray imaging (SG-DFXI). SG-DFXI obtains information related to the sample's small-angle X-ray scattering using a conventional X-ray source and grid. It is specifically utilized to detect low-density materials that are invisible when using conventional techniques. To demonstrate its efficacy, an experiment was conducted with food samples containing low-density FBs such as wood, Styrofoam, pencil lead, and soft plastic. A quantitative evaluation was conducted based on the contrast-to-noise ratio (CNR) and relative contrast gain (RCG). The proposed method detected low-density FBs barely visible in absorption images. Additionally, the CNR values measured in dark-field images were approximately 2.8–10.5 times larger than those in the absorption images, indicating that the proposed approach significantly improved the ability to detect low-density FBs in food samples. The RCG characteristic was improved as the system's autocorrelation length ( ξ G ) increased; the RCG value for ξ G = 453 nm was approximately 2.5 times larger than that for ξ G = 171 nm. • Method detecting low-density foreign bodies (FBs) in food products is proposed. • Single-shot grid-based dark-field X-ray imaging (SG-DFXI) method is used. • SG-DFXI obtains information related to samples' small-angle X-ray scattering. • The experiment used food samples with FBs like wood, Styrofoam, soft plastic, etc. • CNR and relative contrast gain (RCG) were used for quantitative evaluation.