基于改进二维最大类间方差法的白色异性纤维检测算法

    Detection algorithm of white foreign fibers based on improved two-dimensional maximum between-class variance method

    • 摘要: 白色异性纤维的检测是棉花在线检测中的一个难题。通过对白色异性纤维和皮棉灰度直方图的分析,改进了二维Otsu算法,在计算目标和背景的概率和时考虑了二维灰度直方图副对角线区域的概率和,缩小了二维Otsu算法阈值对的取值范围。经过试验表明,与一维Otsu算法和快速二维Otsu算法相比,改进后的二维Otsu算法的准确性和实时性都得到了有效提高,该算法在实际生产中已经得到了成功的应用。

       

      Abstract: The white foreign fibers detection is a difficult problem of the lint online detection. Through the analysis of the 2D gray histogram of white foreign fibers and lint, the two-dimensional Otsu algorithm was improved. This improved algorithm considered the probabilities of the counter-diagonal area in 2D gray histogram when the probabilities of objective and background was calculated, and reduced the range of threshold. The results indicated that the improved algorithm of 2D effectively enhanced the accuracy and real-time property of segmentation comparing with the one-dimensional Otsu algorithm and the fast two-dimensional Otsu algorithm. The improved algorithm has been successfully used in practical production.

       

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