An improved genetic algorithm for optimal feature subset selection from multi-character feature set
Expert Systems with Applications: An International Journal
Computers and Electronics in Agriculture
Fast recognition of foreign fibers in cotton lint using machine vision
Mathematical and Computer Modelling: An International Journal
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This paper presents an automated visual inspection system for the detection of foreign fibers in lint. The system mainly includes six parts, namely Input Conveyer, Lint Layer Generator, Output Roller, Image Acquisition System, Host Computer and Lint Layer Collector. The lint for inspection is fed into the Lint layer Generator through the Input Conveyer, and then made into uniform thin layer. The generated lint layer are dragged out of the Generator and transferred to the inspection box where two cameras are served for imaging. Live images of lint with foreign fibers are captured by the Image Acquisition System and then processed in the Host Computer using inspection algorithm designed for detection of foreign fibers. The inspection algorithm contains four main steps, namely, image enhancement, segmentation, post-processing and decision-making. Dozens of carefully selected foreign fiber samples were used to test the performance of the automated visual inspection system. The results indicate that the proposed system can detect out most of the foreign fibers mixed in lint correctly.