PC-based machine vision system for real-time computer-aided potato inspection

Rapid and/or nondestructive quality evaluation methods for potatoes: A review

“…Thereafter, studying the potential use of imaging systems in potato sorting and grading were extensively accelerated. Greening, as an external defect, was successfully detected based on tuber surface color by Tao et al (1995a), Zhou et al (1998), Noordam et al (2000, and Dacal-Nieto et al (2009), with classification rates of defected tubers of 90%, 78.0%, 88.1%, and 86.2%, respectively. Sorting and grading tubers could be a difficult mission with the singulation problem as a result of the possible interference between different touching objects (Marchant et al, 1990;Al-Mallahi et al, 2010a).…”

Minimalist AdaBoost for Blemish Identification in Potatoes

“…[6] graded potatoes by size and shape. In [7] a system uses green levels to detect green defects (greening and sprouting) in potatoes. In [8] mis-shapen potatoes are detected by comparing the local rate of change in radius of a potato as well as detecting sprouting by comparing the green colour channel with the intensity.…”

Potato Surface Defect Detection Based on Deep Transfer Learning

“…However, early automated grading systems have extensively utilized image processing algorithms and relied on manually defined image features to build classifiers [12][13][14][15], limiting the robustness and generalization [16] of detection performance due to the variance of potato types, appearances, and damage defects [17]. These machine vision systems form the basis of optical sorters used for potato grading and quality inspection [18][19][20]. For example, Noordam et al develop a high-speed sorter to grade potatoes on on size, shape, and color based on several image processing and classification algorithms: Linear Discriminant Analysis combined with a Mahalanobis distance classifier for color segmentation; a Fourier-based estimator for shape classification; and features such as central moments, area, and eccentricity are used to discriminate between similar colored defects [20].…”