Compact and fast depth sensor based on a liquid lens using chromatic aberration to improve accuracy

色差 光学 景深 镜头(地质) 光学设计 焦点深度(构造) 光学(聚焦) 焦距 实测深度 消色差透镜 计算机科学 色阶 软件 物理 古生物学 俯冲 地球物理学 生物 构造学 程序设计语言
作者
Gyu Suk Jung,Yong Hyub Won
出处
期刊:Optics Express [Optica Publishing Group]
卷期号:29 (10): 15786-15786 被引量:6
标识
DOI:10.1364/oe.425191
摘要

Depth from defocus (DFD) obtains depth information using two defocused images, making it possible to obtain a depth map with high resolution equal to that of the RGB image. However, it is difficult to change the focus mechanically in real-time applications, and the depth range is narrow because it is inversely proportional to the depth accuracy. This paper presents a compact DFD system based on a liquid lens that uses chromatic aberration for real-time application and depth accuracy improvement. The electrical focus changing of a liquid lens greatly shortens the image-capturing time, making it suitable for real-time applications as well as helping with compact lens design. Depth accuracy can be improved by dividing the depth range into three channels using chromatic aberration. This work demonstrated the improvement of depth accuracy through theory and simulation and verified it through DFD system design and depth measurement experiments of real 3D objects. Our depth measurement system showed a root mean square error (RMSE) of 0.7 mm to 4.98 mm compared to 2.275 mm to 12.3 mm in the conventional method, for the depth measurement range of 30 cm to 70 cm. Only three lenses are required in the total optical system. The response time of changing focus by the liquid lens is 10 ms, so two defocused images for DFD can be acquired within a single frame period of real-time operations. Lens design and image processing were conducted using Zemax and MATLAB, respectively.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
斯文败类应助Berne采纳,获得10
刚刚
布同完成签到,获得积分0
刚刚
科研通AI6.3应助alex_wang采纳,获得10
刚刚
1秒前
1秒前
繁荣的飞雪完成签到,获得积分20
3秒前
王梦茹发布了新的文献求助10
4秒前
仟111完成签到 ,获得积分10
5秒前
5秒前
6秒前
6秒前
勤劳的水杯完成签到,获得积分10
8秒前
天涯飞虎发布了新的文献求助10
9秒前
orixero应助szz采纳,获得10
9秒前
zlk关闭了zlk文献求助
9秒前
研友_Lw7MKL发布了新的文献求助10
9秒前
赘婿应助黄瓜橙橙采纳,获得10
10秒前
赘婿应助和谐的鲜花采纳,获得10
10秒前
chen发布了新的文献求助10
10秒前
10秒前
希望天下0贩的0应助松林采纳,获得10
11秒前
科研通AI6.3应助松林采纳,获得10
11秒前
12秒前
13秒前
14秒前
乐乐应助wujiwuhui采纳,获得10
14秒前
管ws完成签到 ,获得积分10
15秒前
chen完成签到,获得积分10
15秒前
花果山发布了新的文献求助10
16秒前
Berne发布了新的文献求助10
17秒前
佰斯特威应助科研通管家采纳,获得10
17秒前
彭于晏应助科研通管家采纳,获得10
17秒前
自由飞翔应助科研通管家采纳,获得10
17秒前
领导范儿应助科研通管家采纳,获得10
18秒前
传奇3应助科研通管家采纳,获得20
18秒前
我是老大应助科研通管家采纳,获得10
18秒前
18秒前
18秒前
cx应助科研通管家采纳,获得10
18秒前
汉堡包应助科研通管家采纳,获得10
18秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Les Mantodea de Guyane: Insecta, Polyneoptera [The Mantids of French Guiana] 2500
Atlas of Aligner Treatment and Planning A Case-Based Approach 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Soil mites of the family Rhagidiidae (Actinedida: Eupodoidea). Morphology, Systematics, Ecology 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Decoding Sensitive Skin Syndrome: International Expert Advisory Insights on Management From India and the United States of America 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7437063
求助须知:如何正确求助?哪些是违规求助? 9038534
关于积分的说明 19261227
捐赠科研通 7063154
什么是DOI,文献DOI怎么找? 3237573
关于科研通互助平台的介绍 2400941
邀请新用户注册赠送积分活动 2221442