A New High-Speed Foreign Fiber Detection System with Machine Vision
Author(s) -
Zhiguo Chen,
Wenbo Xu,
Leng Wen-hao,
Yi Fu
Publication year - 2010
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2010/398364
Subject(s) - computer science , computer vision , artificial intelligence , field programmable gate array , machine vision , fiber , optical fiber , block (permutation group theory) , segmentation , digital signal processing , lens (geology) , digital image processing , image processing , computer hardware , engineering , materials science , image (mathematics) , mathematics , telecommunications , geometry , petroleum engineering , composite material
A new high-speed foreign fiber detection system with machine vision is proposed for removing foreign fibers from raw cotton using optimal hardware components and appropriate algorithms designing. Starting from a specialized lens of 3-charged couple device (CCD) camera, the system applied digital signal processor (DSP) and field-programmable gate array (FPGA) on image acquisition and processing illuminated by ultraviolet light, so as to identify transparent objects such as polyethylene and polypropylene fabric from cotton tuft flow by virtue of the fluorescent effect, until all foreign fibers that have been blown away safely by compressed air quality can be achieved. An image segmentation algorithm based on fast wavelet transform is proposed to identify block-like foreign fibers, and an improved canny detector is also developed to segment wire-like foreign fibers from raw cotton. The procedure naturally provides color image segmentation method with region growing algorithm for better adaptability. Experiments on a variety of images show that the proposed algorithms can effectively segment foreign fibers from test images under various circumstances
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