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中文摘要：
分析了磨粒的自动识别研究在铁谱技术发展和应用中的重要性。指出铁谱磨粒图像分割是磨粒自动识别的重要环节，铁谱图像所包含的彩色信息对磨粒识别和磨损形式分析非常重要。将最小二乘支持向量机LSSVM用于彩色磨粒图像的分割，利用模糊c均值选取训练样本，把磨粒图像的R，G，B分量，同一像素点各分量的方差以及像素点邻域像素均值作为特征。对彩色磨粒图像分割，取得了很好的效果，为磨粒自动识剐提供了更有效的信息。
英文摘要：
The importance of wear debris intelligent recognition for the development and application of ferrography was analyzed. It was pointed out that the segmentation method of ferrograph debris image was important for wear debris intelligent recognition because the color information contained in ferrograph image was important to particle identification and wear form analysis. The least square support vector machine （LS-SVM） was used in the segmentation of color image. The training data was acquired with the help of fuzzy c-means （FCM） algorithm, and then the R, G, B components, the component variance of same pixel point and the average of neighborhood pixels were taken as the identification characteristics. Finally the color image of ferrography was segmented with a good effect, which brought useful information for the intelligent recognition of wear debris.
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