In this paper, we study a food ingredient processing that has a total of ten fabrication stages, where the first stage is known as crystal seed count. In this stage, manufacturers study under a microscope the food sample and count crystal seeds per unit area. Sample preparation has imperfections (e.g. air bubbles) that need to be disregarded. The number of seed crystals per unit area is a key indicator for the quality of subsequent processing steps. This paper proposes a method for automating the crystal counting and air bubble removal processes in the seed count stage, in order to save manufacturers considerable time and money. An automated image processing pipeline for crystal counting and air bubble removal is employed in the proposed method. In addition to the proposed pipeline for crystal counting and air bubble removal automation, we also introduce an interactive GUI which is operated based on this pipeline. This GUI can not only be used by manufacturers of the particular crystals that we examine in this paper, but can also benefit other manufacturers in the food industry that face similar issues. By utilizing this automatic crystal counting pipeline and GUI, food crystal fabrication can be made more efficient. This paper contributes to the field of food processing by presenting a practical and innovative solution to a common challenge in the industry.
Qiyue Liang, Ali Shakouri, Jan P. Allebach, "Analysis of food processing crystal images" in Electronic Imaging, 2023, pp 196-1 - 196-8, https://doi.org/10.2352/EI.2023.35.15.COLOR-196