Segmentation of LED Pixel Matrix by Using Optimal Threshold Method with Area Constraint

YU Hong-chun; DENG Yi-cheng; ZHENG Xi-feng

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Segmentation of LED Pixel Matrix by Using Optimal Threshold Method with Area Constraint

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- Segmentation of LED Pixel Matrix by Using Optimal Threshold Method with Area Constraint
- Chinese Journal of Liquid Crystals and Displays Vol. 27, Issue 5, Pages: 653-657(2012)
- 作者机构：
  
  1. 中国科学院长春光学精密机械与物理研究所,吉林长春,中国,130033
  2. 中国科学院研究生院北京,100049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN312+.8
- Received：11 April 2012，
  
  Revised：15 June 2012，
  
  Published：15 October 2012
- 稿件说明：
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于洪春, 邓意成, 郑喜凤. 面积约束下的最优阈值法分割LED像素点阵[J]. 液晶与显示, 2012,(5): 653-657

YU Hong-chun, DENG Yi-cheng, ZHENG Xi-feng. Segmentation of LED Pixel Matrix by Using Optimal Threshold Method with Area Constraint[J]. , 2012,(5): 653-657
于洪春, 邓意成, 郑喜凤. 面积约束下的最优阈值法分割LED像素点阵[J]. 液晶与显示, 2012,(5): 653-657 DOI：

YU Hong-chun, DENG Yi-cheng, ZHENG Xi-feng. Segmentation of LED Pixel Matrix by Using Optimal Threshold Method with Area Constraint[J]. , 2012,(5): 653-657 DOI：

摘要

针对基于CCD相机采集方式的亮度校正方法需要从采集图像中分割出每颗LED像素的亮度信息的问题

提出面积约束下的最优阈值分割法。在最优阈值分割法的基础上

根据先验信息引入面积约束条件

对阈值的取值范围进行约束。与传统的最优阈值法相比可以避免分割后LED像素区域连接的情况。面积约束下的最优阈值分割法生成采集图像的灰度直方图

利用最优阈值算法结合面积约束生成最优阈值

最后通过图像的阈值分割法将采集图像分割。实验表明

该方法可以比较好地分割出采集图像中的LED像素

并可避免当LED像素点分布密集时应用最优阈值法分割LED像素造成的区域连接问题。

Abstract

In order to segment each LED pixels from the image which is acquired by CCD and is used to brightness correction

a method based on optimal threshold segmentation with area constraint has been proposed. Based on optimal threshold method

taking prior information into account

an area constraint is introduced to restrain the range of threshold. Compared with traditional method

it is well done to avoid the LED region segmented connecting together. In the optimal threshold method with area constraint

the histogram of the captured image is generated

using the method of optimal threshold with area constraint

the optimal threshold is acquired. Finally

the optimal threshold method is used to segment the captured image. Experiments demonstrate that it is good to use this method to segment the LED pixels from the captured image

and also it can avoid the segmented region of LED pixels with a dense distribution connecting together.

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Keywords

references

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