This paper describes the research approach to identify the contaminants which have similar color to the background wool and their removal from wool in real time. First, different light source is sought for getting the high contrast image between wool and contaminants. Second, different CCD detector including infrared camera, monochrome area scan camera was tried for identification of white contaminants. Relative infrared theory and spectral theory are also presented. Third, different image processing algorithms including threshold in HSV color space, local adaptive threshold, region-growing algorithm and their comparisons are presented. The combination of local adaptive threshold and global threshold algorithms can well identify most of white contaminants. At last, a research approach on contaminant removal from wool by the image processing algorithm in real time is presented. Both software and hardware approach are reported.
The traditional method for the evaluation of cashmere quality is subjective and low in accuracy. In this paper, a computer vision system is presented for the objective identification and classification of pigmented fibres, which consists of a web maker, an image acquisition system and a computer for image processing. The techniques of fibre preparation, image acquisition and the development of suitable algorithm together with software for removal of the background fibres and counting of pigmented fibres, are described in detail.