Visibility Classification of Pellets in Piles for Sizing without Overlapped Particle Error

Abstract

Abstract

Visibility Classification of Rocks in Piles

“…In earlier work [4], where we presented methods for visibility classification of pellets in piles, features with scale were used. The features visibility ratio, equivalent area diameter, minor axis and major axis were effective to discriminate between entirely and partially visible pellets.…”

“…To minimize overlapped particle error, Thurley and Ng have presented work where a 3D feature called visibility ratio have been used to classify the visibility of rocks [18]. In earlier work we have classified pellets on a surface of a pile into entirely and partially visible pellets to overcome overlapped particle error [4].…”

An industrial 3D vision system for size measurement of iron ore green pellets using morphological image segmentation

“…The non-perpendicular aspect ratio is equal to the major axis divided by the minor axis where the major and minor axes do not have to be perpendicular. A subsequent more rigorous investigation of visibility classification using a range of features is presented by Andersson et al (2007b).…”

Computer Vision-based Monitoring of Harvest Quality

“…Firstly, an industry with numerous works covering quality is material aggregates. In [85,86] the authors estimated the PSD of iron ore transported on a conveyor belt based on shape and size features. A number of handcrafted features are extracted to train an SVM for estimation of iron ores on a conveyor in [87].…”