An improved floc segmentation algorithm based on PSO and OSTU

XIE Xin; WANG Jian-bin; HU Feng-ping

doi:10.13873/J.1000-9787(2015)01-0131-04

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An improved floc segmentation algorithm based on PSO and OSTU

更新时间：2025-09-11

- An improved floc segmentation algorithm based on PSO and OSTU
- Vol. 34, Issue 1, Pages: 131-134(2015)
- 作者机构：
  
  1. 华东交通大学信息工程学院
  2. 华东交通大学土木建筑学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2015)01-0131-04
  CLC： TP391.41
- Published：2015
- 稿件说明：
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[1]谢昕,王建宾,胡锋平.一种基于PSO与OSTU的改进絮体分割算法[J].传感器与微系统,2015,34(01):131-134.

XIE Xin, WANG Jian-bin, HU Feng-ping. An improved floc segmentation algorithm based on PSO and OSTU[J]. 2015, 34(1): 131-134.
[1]谢昕,王建宾,胡锋平.一种基于PSO与OSTU的改进絮体分割算法[J].传感器与微系统,2015,34(01):131-134. DOI： 10.13873/J.1000-9787(2015)01-0131-04.

XIE Xin, WANG Jian-bin, HU Feng-ping. An improved floc segmentation algorithm based on PSO and OSTU[J]. 2015, 34(1): 131-134. DOI： 10.13873/J.1000-9787(2015)01-0131-04.

摘要

介绍了图像分割中常用的直方图法、迭代法、经典大津法的阈值选取原理

然后对水处理混凝过程中的絮体图像进行分割对比实验

结合絮体运动特点和水处理实时性的要求

提出了一种基于粒子群优化（PSO）与OSTU的絮体图像分割的改进算法

即先通过灰度拉伸以增强图像灰度对比

再利用PSO算法的全局搜索能力来改善OSTU方法的阈值选取时间

求出分割阈值。实验表明:该算法能实现絮体图像的准确、快速分割

达到实时计算絮体等效粒径和数量的要求。

Abstract

Introduce threshold value selection principle such as histogram

iterative and classic OSTU method

then use these three methods to divide flocs image of water treatment coagulation process

by comparing the effect and combining the floc movement and the characteristics of the real-time demand in water treatment

put forward a kind of improved OSTU image segmentation method based on particle swarm optimization（ PSO）. First

using gray stretch to enhance image gray-scale contrast and then utilizing global search ability of PSO algorithm to improve threshold value time of reinforced OSTU method and get segmentation threshold. Experimental results show that the algorithm can realize accurate and fast segmentation of flocs in water treatment

reach requirement of realtime calculation of equivalent size and number of floc.

关键词

Keywords

references

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