A new high-speed foreign fiber detection system with machine vision is proposed for removing\r\nforeign fibers from raw cotton using optimal hardware components and appropriate algorithms\r\ndesigning. Starting from a specialized lens of 3-charged couple device CCD camera, the system\r\napplied digital signal processor DSP and field-programmable gate array FPGA on image\r\nacquisition and processing illuminated by ultraviolet light, so as to identify transparent objects\r\nsuch as polyethylene and polypropylene fabric from cotton tuft flow by virtue of the fluorescent\r\neffect, until all foreign fibers that have been blown away safely by compressed air quality can\r\nbe achieved. An image segmentation algorithm based on fast wavelet transform is proposed\r\nto identify block-like foreign fibers, and an improved canny detector is also developed to\r\nsegment wire-like foreign fibers from raw cotton. The procedure naturally provides color image\r\nsegmentation method with region growing algorithm for better adaptability. Experiments on a\r\nvariety of images show that the proposed algorithms can effectively segment foreign fibers from\r\ntest images under various circumstances.
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