Detection of external defects on potatoes is the most important technology in the realization of automatic potato sorting stations. This paper presents a hierarchical grading method applied to the potatoes. In this work a potato defect detection combining with size sorting system using the machine vision will be proposed. This work also will focus on the mathematics methods used in automation with a particular emphasis on the issues associated with designing, implementing and using classification algorithms to solve equations. In the first step, a simple size sorting based on mathematical binarization is described, and the second step is to segment the defects; to do this, color based classifiers are used. All the detection standards for this work are referenced from the United States Agriculture Department, and Canadian Food Industries. Results show that we have a high accuracy in both size sorting and classification. Experimental results show that support vector machines have very high accuracy and speed between classifiers for defect detection. © 2011 Elsevier Ltd. All rights reserved.
Razmjooy, N., Mousavi, B. S., & Soleymani, F. (2012). A real-time mathematical computer method for potato inspection using machine vision. Computers and Mathematics with Applications, 63(1), 268–279. https://doi.org/10.1016/j.camwa.2011.11.019