Improved Extraction Algorithm of Outside Dividing Lines in Watershed Segmentation Based on PSO Algorithm for Froth Image of Coal Flotation

2014 ◽  
Vol 9 (2) ◽  
Author(s):  
Mu-ling TIAN ◽  
Jie-ming Yang
2021 ◽  
Vol 170 ◽  
pp. 107023
Author(s):  
Zhiping Wen ◽  
Changchun Zhou ◽  
Jinhe Pan ◽  
Tiancheng Nie ◽  
Ruibo Jia ◽  
...  

2012 ◽  
Vol 476-478 ◽  
pp. 867-870
Author(s):  
Jian Zhao ◽  
Ming Yu ◽  
Xin Ke Yu ◽  
Ling Li Zhang ◽  
Xian Guo Yan

It is precondition for realizing the mechanical dynamic optimization design and the dynamic modification to analyze the characteristic of multi-degree-of-freedom system. The paper discusses a kind of modal parameters wavelet transform identification method based on Modified Particle Swarm Optimization (PSO) algorithm, furthermore, proposes the PSO wavelet ridge extraction algorithm, and gives the formulas identifying modal parameters from a wavelet ridge. The proposed method applies to the dynamic characteristic identification of a flow meter to explore the effectiveness. The results prove the method is precision and insensitive to noise.


Author(s):  
Mu-Ling Tian ◽  
Jie-Ming Yang

This paper presents an improved genetic algorithm for the optimization of the structure element used in morphological open and closed filtering. Considering that the evaluation of the froth images of coal flotation is categorized as a no-reference image evaluation, in the optimization of the structural element, a denoising evaluation index of an improved information capacity was used as the adaptation degree function. In addition, this paper proposes the determination method of chromosome length in the structure element optimization algorithm. In the improved genetic algorithm, based on adaptive variation, the variation regulation factor and the mechanism of concentration adjustment are introduced. When compared to an optimization process of the structural element in froth image denoising using the genetic algorithm, the adaptive genetic algorithm, the improved genetic algorithm improves the efficiency and accuracy of the optimization process. It has been proven that optimizing the structural element by the improved genetic algorithm increases fitness and reduces noise when using morphological open and closed reconstruction filters.


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