Classification between digs and dust particles on optical surfaces with acquisition and analysis of polarization characteristics

旋光法 光学 极化(电化学) 物理 线极化 穆勒微积分 遥感 散射 计算机科学 激光器 地质学 化学 物理化学
作者
Fan Wu,Yongying Yang,Jiabin Jiang,Pengfei Zhang,Yanwei Li,Xiao Xiang,Guo‐Hua Feng,Jian Bai,Kaiwei Wang,Qiao Xu,Hongzhen Jiang,Bo Gao
出处
期刊:Applied Optics [Optica Publishing Group]
卷期号:58 (4): 1073-1073 被引量:24
标识
DOI:10.1364/ao.58.001073
摘要

In the automatic detection for surface defects of optical components, the digs and dust particles exhibit similar features: point-like shape and variable intensity reflectivity. On this condition, these two types with entirely different damages are easily confused so that misjudgments will be induced. To solve this problem, a polarization-characteristics-based classification method of digs and dust particles (PCCDD) is proposed based on the polarimetric imaging technique and dark-field imaging technique. First, a dark-field imaging system equipped with a polarization state generator (PSG) and a polarization state analyzer (PSA) is employed to measure and establish normalized Mueller matrices' datasets of digs and dust particles. And by a nonlinear global search combined with a separability evaluation method, the optimal number of acquisitions and corresponding polarization measurement states of the PSG and the PSA are obtained, as well as the parameters of classification function. Then, multiple polarization images are acquired under the optimal states to extract a multidimensional feature description that relates only to the polarization characteristics of the defect; this subsequently acts as the input vector of the classifier to finally achieve the classification. This method takes full advantage of both the difference in polarization properties between digs and dust particles and the characteristic that the polarization properties of digs are relatively invariant while those of dust particles have a large variability. The classification process involves only simple matrix operations. Compared to the traditional discrimination method based on intensity images, the features obtained by this method have a higher separability. Experiments show that the classification accuracy reaches over 90%. This method can be further applied to the recognition and discrimination of other defects in the field of surface defects' detection.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
20011013完成签到 ,获得积分10
1秒前
2秒前
量子星尘发布了新的文献求助10
3秒前
5秒前
华仔应助机灵飞阳采纳,获得10
6秒前
潘善若发布了新的文献求助10
6秒前
7秒前
陈少华完成签到 ,获得积分10
7秒前
下一秒发布了新的文献求助10
8秒前
杨乃彬完成签到,获得积分10
8秒前
取名叫做利完成签到,获得积分10
9秒前
赘婿应助喻义梅采纳,获得10
10秒前
小二郎应助小门采纳,获得10
11秒前
ll发布了新的文献求助10
14秒前
正直的鸿完成签到,获得积分10
19秒前
20秒前
万能图书馆应助高贵梦露采纳,获得10
21秒前
momo发布了新的文献求助10
23秒前
传奇3应助boltos采纳,获得10
24秒前
24秒前
25秒前
要减肥笑阳完成签到 ,获得积分10
26秒前
全若之发布了新的文献求助10
31秒前
Jasper应助momo采纳,获得10
33秒前
Kasom完成签到 ,获得积分10
40秒前
顺利一德完成签到,获得积分20
41秒前
香蕉觅云应助Afaq采纳,获得10
41秒前
41秒前
41秒前
manman完成签到,获得积分10
42秒前
42秒前
哈哈哈完成签到,获得积分10
42秒前
YamDaamCaa应助科研通管家采纳,获得30
43秒前
43秒前
领导范儿应助科研通管家采纳,获得10
43秒前
香蕉觅云应助科研通管家采纳,获得10
43秒前
43秒前
大个应助科研通管家采纳,获得10
43秒前
czh应助科研通管家采纳,获得20
43秒前
科研通AI2S应助科研通管家采纳,获得10
43秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
‘Unruly’ Children: Historical Fieldnotes and Learning Morality in a Taiwan Village (New Departures in Anthropology) 400
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3989263
求助须知:如何正确求助?哪些是违规求助? 3531418
关于积分的说明 11253814
捐赠科研通 3270066
什么是DOI,文献DOI怎么找? 1804884
邀请新用户注册赠送积分活动 882084
科研通“疑难数据库(出版商)”最低求助积分说明 809136