Intraoral 3D measurement with group-multiline coding and feature enhancement

CHEN Ziyan; CHEN Sheng

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Intraoral 3D measurement with group-multiline coding and feature enhancement

Optical Sensing and Measurement | 更新时间：2026-05-20

- Intraoral 3D measurement with group-multiline coding and feature enhancement
- OPTICAL TECHNIQUE Vol. 52, Issue 3, Pages: 257-265(2026)
- 作者机构：
  
  上海理工大学光电信息与计算机工程学院，上海 200082
- 作者简介：
- 基金信息：
- DOI：
  CLC： TH741;TP391.4
- Received：26 December 2025，
  
  Revised：2026-02-12，
  
  Published：20 May 2026
- 稿件说明：
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陈梓焱,陈胜.基于分组多线编码与特征增强的口内三维测量技术[J].光学技术,2026,52(03):257-265.

CHEN Ziyan,CHEN Sheng.Intraoral 3D measurement with group-multiline coding and feature enhancement[J].OPTICAL TECHNIQUE,2026,52(03):257-265.
陈梓焱,陈胜.基于分组多线编码与特征增强的口内三维测量技术[J].光学技术,2026,52(03):257-265. DOI：

CHEN Ziyan,CHEN Sheng.Intraoral 3D measurement with group-multiline coding and feature enhancement[J].OPTICAL TECHNIQUE,2026,52(03):257-265. DOI：

摘要

为解决现有口内扫描技术在牙齿散射、设备抖动及金属反光等复杂环境下存在的图像质量差、测量精度下降问题，提出一种新型结构光扫描方法。首先

采用分组多线编码算法代替传统的正弦或格雷码编码进行条纹解码。通过加大相邻条纹之间的距离

有效抑制牙齿表面的散射

同时规避了相位计算方法中因扫描仪抖动导致的精度下降问题。其次

提出一种一致条纹特征增强（CSFE）方法

自适应的增强镜面反射、曝光不足以及低对比度区域的条纹特征

从而在每个场景中重建更多有效和准确的点。实验结果表明

采用新算法的设备使口内3D测量的精度提高至15~25μm

测量效率提升了40%，全牙弓点云配准的失败场景数降低约40%。

Abstract

To address the problems of poor image quality and degraded measurement accuracy in existing intraoral scanning technologies under complex conditions such as tooth scattering

scanner jitter

and metal reflections

a novel structured light scanning method is proposed. First

a group-multiline coding algorithm for fringe decoding is introduced to replace traditional sinusoidal or Gray code encoding. By increasing the distance between adjacent fringes

this algorithm effectively suppresses scattering on tooth surfaces while circumventing accuracy degradation caused by scanner jitter in phase calculation methods. Second

a Consistent Stripe Feature Enhancement （CSFE） method is proposed to adaptively enhance stripe features in regions with mirror reflections

underexposure

and low contrast

thereby reconstructing more valid and accurate points for each scene. Experimental results demonstrate that the proposed method improves the accuracy of intraoral 3D measurement to 15~25 μm

increases measurement efficiency by 40%

and reduces the number of failed full-arch point cloud registration scenarios by approximately 40%.

关键词

Keywords

references

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