Design of Sesame Peeling Machine and Performance Analysis with Threshold-Based Image Segmentation Technique

Abstract

In this study, peeled sesame seeds were analyzed using a threshold-based image segmentation technique. Peeled sesame seeds were obtained from a sesame membrane peeling machine whose design and production was carried out within the project's scope. By applying the image segmentation technique to the samples taken from the machine, the machine's sesame peeling performance and sesame peeling percentage were determined. Automatic calculation of the peeled sesame weights in the image is presented by the threshold-based image segmentation technique, which is one of the basic operations of digital image processing and is extensively employed in many application areas, including extraction, detection, and identification of features. This technique aims to divide an image into meaningful regions according to a particular operation. Based on the results obtained using the threshold-based image segmentation technique, the success achieved in the peeling process is 48%, 56%, 60% for periods of 60 min, 120 min, 180 min respectively. By using the designed machine, the processing time of peeling sesame has been reduced by 75%, water consumption has been reduced by 90%, and salt use has been eliminated. Moreover, operating, personnel, and energy costs have been minimized.