Separating and clustering of structured light stripe color

LI Hua; YANG Fan; YANG Hua-min; HAN Cheng; ZHANG Chao

doi:10.3788/OPE.20162405.1206

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Separating and clustering of structured light stripe color

更新时间：2020-08-13

- Separating and clustering of structured light stripe color
- Optics and Precision Engineering Vol. 24, Issue 5, Pages: 1206-1214(2016)
- 作者机构：
  
  1. 长春理工大学计算机科学技术学院,吉林长春,130000
  2. 特种电影技术及装备国家地方联合工程研究中心,吉林长春,130000
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20162405.1206
  CLC： TN919.8;TP391
- Received：05 January 2016，
  
  Revised：07 March 2016，
  
  Published：25 May 2016
- 稿件说明：
移动端阅览
李华, 杨帆, 杨华民等. 条纹颜色分离与聚类[J]. 光学精密工程, 2016,24(5): 1206-1214

LI Hua, YANG Fan, YANG Hua-min etc. Separating and clustering of structured light stripe color[J]. Editorial Office of Optics and Precision Engineering, 2016,24(5): 1206-1214
李华, 杨帆, 杨华民等. 条纹颜色分离与聚类[J]. 光学精密工程, 2016,24(5): 1206-1214 DOI： 10.3788/OPE.20162405.1206.

LI Hua, YANG Fan, YANG Hua-min etc. Separating and clustering of structured light stripe color[J]. Editorial Office of Optics and Precision Engineering, 2016,24(5): 1206-1214 DOI： 10.3788/OPE.20162405.1206.

摘要

为解决彩色物体表面颜色干扰以及条纹之间的颜色串扰导致彩色结构光系统产生的条纹颜色误识别问题

提出了彩色结构光的条纹颜色分离以及聚类方法。首先

提出了一种新的摄像机和投影机的颜色校正方法

以消除外界环境光以及系统的颜色串扰现象

解决系统的耦合性问题。其次

给出了一种物体的反射分离机制

用于提取物体表面的漫反射分量和镜面反射分量

修正彩色物体的背景色对彩色编码条纹的影响。最后

利用颜色聚类算法

对经过彩色物体调制后的条纹进行颜色归类划分

纠正条纹颜色之间的干扰

恢复系统消耗的彩色条纹颜色信息。实验验证了本文提出方法的有效性

结果表明:该方法具有较高的抗干扰能力、较强的鲁棒性

能准确有效地识别受干扰的彩色条纹

识别正确率达到92%左右。

Abstract

To overcome the misrecognition for the stripe color from a color structure light system caused by the interference of object surface color and the color crosstalk among the stripes

a method to separate and cluster the structured light stripe color was proposed. Firstly

a novel color correction method for a camera and a projector was designed to avoid the crosstalk phenomenon of color sequence from ambient light and the system and to solve the coupling issues of the system. Then

a reflective separation mechanism was presented to extract the diffuse component and the specular component of object surfaces and to correct the effect of object background color on color-coded stripes. Finally

the color clustering algorithm was used to classify the modulated stripe color and to correct the interference among stripes and recover the information of stripe color due to energy consumption of the system. The feasibility of the proposed method was verified. Experimental results show that this method has higher anti-jamming capability and stronger robustness. It recognizes correctly the interfered colored stripes

and the recognition rate reaches about 92%.

关键词

Keywords

references

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