王 冬, 尹伯彪, 刘 翔, 何相呈, 苏真伟. 棉花中白色异性纤维的线扫描激光成像检测方法[J]. 农业工程学报, 2015, 31(9): 310-314. DOI: 10.11975/j.issn.1002-6819.2015.09.046
    引用本文: 王 冬, 尹伯彪, 刘 翔, 何相呈, 苏真伟. 棉花中白色异性纤维的线扫描激光成像检测方法[J]. 农业工程学报, 2015, 31(9): 310-314. DOI: 10.11975/j.issn.1002-6819.2015.09.046
    Wang Dong, Yin Bobiao, Liu Xiang, He Xiangcheng, Su Zhenwei. Laser line scan imaging method for detection of white foreign fibers in cotton[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 31(9): 310-314. DOI: 10.11975/j.issn.1002-6819.2015.09.046
    Citation: Wang Dong, Yin Bobiao, Liu Xiang, He Xiangcheng, Su Zhenwei. Laser line scan imaging method for detection of white foreign fibers in cotton[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015, 31(9): 310-314. DOI: 10.11975/j.issn.1002-6819.2015.09.046

    棉花中白色异性纤维的线扫描激光成像检测方法

    Laser line scan imaging method for detection of white foreign fibers in cotton

    • 摘要: 在可见光和紫外光照明条件下,皮棉中白色异性纤维和棉花背景的颜色相近,很难用现有的机器视觉系统或人工方法检测出来。该文以12种典型白色异性纤维为样本,采用线扫描相机,分别在红色激光(波长658 nm)、蓝色激光(波长405 nm)和红外激光(波长850 nm)3种照明条件下,改变激光功率和曝光时间,获取了300幅白色异性纤维与棉花的图像。在此基础上,根据同一图像中目标和背景的平均灰度值计算了图像的对比度,然后作出了不同激光波长、功率、曝光时间和图像对比度之间的关系曲线,最后,在该试验装置的条件下,该文确定了线激光成像的最佳检测波长为658 nm、光功率为55 mW和曝光时间为36 μs,发现采用优化的线激光参数成像,图像中12种白色异性纤维灰度值已经接近饱和而棉花还处于欠饱和状态,"目标"和"背景"的对比度达到最大,利用两者平均灰度值的明显差异可以检测出棉花中的白色异性纤维。试验结果表明,采用优化的线激光成像参数获取730幅棉花图像,利用简单的Prewitt算子边缘检测法和固定阈值的二值化方法对图像进行分割,12种典型白色异性纤维样本的正确识别率分别可达93.7%和92.9%。

       

      Abstract: Abstract: With the development of machine vision systems, auto-sorting systems have been used for removal of foreign fibers (contaminants) in cotton. Of them, white foreign fibers are hardly distinguished from lint cotton because their colors are the same or very close under the illumination of visible lights and ultraviolet lights in the inspection by an existing machine vision system or manual sorting. The laser imaging methods previously suggested by our team can detect most of the white foreign fibers in cotton, but there are 2 problems that need to be solved: One is that they can only use area cameras for the inspection, which is not suitable for the processing line of the lint cotton in textile industry; the other is that the optimization of parameters for the laser imaging system is only concerned with the camera exposure time, but not concerned with the wavelength and the power of the line laser. To solve the 2 problems, in this paper, 12 kinds of typical non-fluorescent white foreign fibers random distributed on the cotton surface were driven by a conveyor, and 300 frames of their images were obtained by a high-speed line-scan camera under the illuminations of line laser at the wavelengths of 658, 405 and 850 mm with different laser light powers and different exposure time individually. Firstly, the contrast of the white foreign fibers and cotton background in a frame of the laser image was quantized by the difference of their average pixel values. Then, the relationship curves between the quantized differences of fiber and cotton grey values and the laser light's wavelengths, the laser light's powers and the exposure time were plotted and analyzed. It was found that using the optimized imaging parameters, the gray level of the foreign fibers had reached a saturated status, but the gray value of cotton was still unsaturated. Thus, by the significant difference of the targets and background, the white foreign fibers could be separated from the cotton. In the experimental imaging system, the image contrast of 12 kinds of white foreign fibers and cotton background had reached a maximum value when the laser images were obtained under the illumination of the line laser at the wavelength of 650 nm with the power of 55 mW and the exposure time of 36 μs. Finally, using the optimized laser imaging system and the traditional imaging system of LED plus ultraviolet light individually, 730 frames of the images of 12 kinds of white foreign fibers with lint cotton were obtained. The experimental results indicated that, the 12 kinds of white foreign fibers could be easily distinguished from cotton. With the optimized imaging system, using a simple algorithm of Prewitt edge detecting or fixed binary segmentation, the successful detecting rate was up to 93.7% or 92.9%, respectively.

       

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