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Research on settlement particle recognition based on fuzzy comprehensive evaluation method

机译:基于模糊综合评价方法的沉降粒子识别研究

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Abstract In order to solve the problems of the laser scattering rate of settlement particles during sedimentation, such as polymerization, coverage, and disappearance, the grayscale characteristics, morphological features, and motion characteristics of the settlement particles are analyzed and studied in this paper. On the basis of these, the recursive idea is applied to the multi-threshold segmentation algorithm with fuzzy 3-partition entropy algorithm, and then, the fuzzy comprehensive evaluation method is used to identify the settlement particles. Finally, the proposed method is implemented in MATLAB 9 and compared with the traditional Kalman filtering and Otsu segmentation algorithm. The experimental results show that the proposed algorithm is better than other algorithms on the ROC curve, and the recognition rate of the settling particles is higher.
机译:摘要为了解决沉降期间沉降颗粒的激光散射速率问题,例如聚合,覆盖和消失,分析沉降颗粒的灰度特性,形态特征和运动特性,并在本文中进行了研究。在这些方面,递归思想应用于具有模糊3分区熵算法的多阈值分割算法,然后使用模糊综合评估方法来识别沉降粒子。最后,所提出的方法在Matlab 9中实现,并与传统的卡尔曼滤波和OTSU分段算法进行比较。实验结果表明,该算法比ROC曲线上的其他算法更好,沉降颗粒的识别率较高。

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