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.
Highlights
The traditional methods of settlement particle size detection include the sieving method and the laser method
Many scholars have studied the algorithm of particle recognition based on image analysis, which improves the efficiency of recognition and the accuracy greatly
Wen et al realized the identification and classification of different rice grains based on the technology of computer image processing technology [9]
Summary
The traditional methods of settlement particle size detection include the sieving method and the laser method. Many scholars have studied the algorithm of particle recognition based on image analysis, which improves the efficiency of recognition and the accuracy greatly. It has become a hot research focus in recent years [1,2,3,4,5,6,7]. The recursive algorithm is designed for the fuzzy 2-partition of the trapezoid membership function, and the segmentation accuracy is low. A multi-threshold segmentation method with recursive fuzzy 3-partition entropy is proposed, and the S membership function containing three. 2.1 Grayscale characteristics of settlement particles The most obvious and intuitionistic characteristic in the image of settlement particles is the grayscale characteristics
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