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High-precision visual localization based on an improved shape-based matching algorithm

APPLIED OPTICS 2021年第5期60卷 1294-1303页

作者： Hu, Shanshan Li, Dan Hong, Mingfeng Wang, Bing Xu, Xiangrong Anhui Univ Technol Sch Elect Informat & Engn Maanshan 243032 Anhui Peoples R China Anhui Univ Coinnovat Ctr Informat Supply & Assurance Technol Hefei 230601 Anhui Peoples R China Anhui Univ Technol Sch Mech Engn Maanshan 243032 Anhui Peoples R China

To deal with the requirement of high-precision localization of large-size workpieces in an industrial environment, an improved shape-based matching algorithm is proposed based on the phase stretching transformation and the iterative closest point algorithms. Basler industrial cameras are used to collect images of large-size workpieces, such as glass. The experimental results show that the average localization error is 0.05 +/- 0.013 mm, which can meet the requirements of practical applications. This algorithm can effectively and accurately achieve high-precision localization of different positions of multi-directionally transformed objects in industrial environments. (C) 2021 Optical Society of America

关键词： Digital imaging Edge detection image compression image processing image processing algorithms Machine vision

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Real-time display camera communication system based on LED displays and smartphones

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OPTICS EXPRESS 2021年第15期29卷 23558-23568页

作者： Bao, Xingyu Pan, Junxing Cai, Zetao Li, Jingwen Huang, Xia Chen, Renzhang Fang, Junbin Jinan Univ Guangzhou 510632 Peoples R China Cyberspace Secur Res Ctr Peng Cheng Lab Shenzhen 518055 Peoples R China Guangdong Prov Engn Technol Res Ctr Visible Light Guangzhou 510632 Peoples R China Guangzhou Municipal Key Lab Engn Technol Visible Guangzhou 510632 Peoples R China

Visible light communication based on display and camera can simultaneously provide the functionalities of display and invisible intbrmation transmission. There are widely potential applications in information broadcasting, stealth advertising, etc. In this paper, a real-time display camera communication system based on LED displays and smartphones is proposed. To solve the rate mismatch problem and the symbol unsynchronization problem between the LED display panel with a relatively high frame rate and the smartphones' camera with a relatively low frame rate, we propose an Alternate Bit-flipping Repeat Coding scheme for adjustable frame rate matching and symbol synchronization with the advantage of eliminating flickers perceivable to human eyes. Fast image processing algorithms are also designed to decrease the computational complexity of extracting information from the captured video frames in real-time. An experimental system was implemented on a 16x16 points LED display panel with a refresh rate of 150 fps and a commercial Android smartphone with an 8 megapixels camera working at 30 fps and a self-developed Android APP. The experimental results show that the real-time LED display camera communication system can achieve a data transmission rate of 30 bps for one LED display point and a maximum distance of 80 cm, and the computational time on the Android smartphone for data receiving is only 11.827 ms. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

关键词： CCD cameras CMOS cameras image processing algorithms image sensors LED displays Visible light communications

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Underwater image sharpening based on structure restoration and texture enhancement

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APPLIED OPTICS 2021年第15期60卷 4443-4454页

作者： Lin, Sen Chi, Kaichen Wei, Tong Tao, Zhiyong Shenyang Ligong Univ Sch Automat & Elect Engn Shenyang 110159 Peoples R China Liaoning Tech Univ Sch Elect & Informat Engn Huludao 125105 Peoples R China Eotvos Lorand Univ Fac Informat H-1117 Budapest Hungary

Light can be absorbed and scattered when traveling through water, which results in underwater optical images suffering from blurring and color distortion. To improve the visual quality of underwater optical images, we propose a novel, to the best of our knowledge, image sharpening method. We utilize the relative total variation model to decompose images into structure and texture layers in a novel manner. On those two layers, the red-blue dark channel prior (RBDCP) and detail lifting algorithms are proposed, respectively. The RBDCP model calculates background light based on brightness, gradient discrimination, and hue judgment, which then generates transmission maps using red-blue channel attenuation characteristics. The linear combination of the Gaussian kernel and binary mask is employed in the proposed detail lifting algorithm. Furthermore, we combine the layers of restoration structure and enhancement texture for image sharpening, inspired by the concept of fusion. Our methodology has rich texture information and is effective in color correction and atomization removal through RBDCP. Extensive experimental results indicate that the proposed method effectively balances image hue, saturation, and clarity. (C) 2021 Optical Society of America

关键词： image metrics image processing image processing algorithms image quality Point spread function Underwater imaging

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Interferometric microscope with a confocal focusing for inner surface defect detection of ICF capsule

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OPTICS EXPRESS 2021年第23期29卷 38924-38938页

作者： Yang, Shuai Liu, Zihao Ma, Xianxian Wang, Qi Wang, Zongwei Wang, Yun Qiu, Lirong Zhao, Weiqian Beijing Inst Technol Sch Optoelect Beijing Key Lab Precis Optoelect Measurement Inst Beijing 100081 Peoples R China China Acad Engn Phys Laser Fus Res Ctr POB 919-987 Mianyang 621900 Sichuan Peoples R China

Inner surface defects of inertial confinement fusion (ICF) capsule are a key factor leading to ignition failure;however, there are still no effective and non-destructive detection methods available. To solve this problem, we propose the first interferometric microscope with confocal focusing (CFIM). CFIM first uses confocal technology to achieve accurate axial positioning of both capsule and the camera, thereby ensuring that the inner surface of the capsule is precisely and clearly imaged at the camera. Then, phase-shifting interferometry based on a short-coherence source and a spherical reference is applied to obtain inner defects result from null inner surface interferograms. In addition, in-situ focusing is realized by the axial adjustment of camera, but not by the capsule, to ensure that the outer defects and the fake inner defects caused by it have the same pixel coordinates, thereby solving the confusion of fake inner defects. The comparative experimental results of the CFIM and the scanning electron microscope (destructive detection) prove the feasibility of the proposed method. With unique precision confocal focusing and in-situ focusing ability, CFIM provides the first approach for non-destructive detection of inner surface defects of ICF capsule to the best of our knowledge. (C) 2021 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Confocal microscopy Digital image processing image processing algorithms Laser beams Phase shifting interferometry Scanning electron microscopy

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Connectivity-based deep learning approach for segmentation of the epithelium in in vivo human esophageal OCT images

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BIOMEDICAL OPTICS EXPRESS 2021年第10期12卷 6326-6340页

作者： Yang, Ziyun Soltanian-Zadeh, Somayyeh Chu, Kengyeh K. Zhang, Haoran Moussa, Lama Watts, Ariel E. Shaheen, Nicholas J. Wax, Adam Farsiu, Sina Duke Univ Dept Biomed Engn Durham NC 27708 USA Univ North Carolina Ctr Esophageal Dis & Swallowing Chapel Hill NC 27599 USA Duke Univ Sch Med Dept Ophthalmol Durham NC 27710 USA

Optical coherence tomography (OCT) is used for diagnosis of esophageal diseases such as Bar rett's esophagus. Given the large volume of OCT data acquired, automated analysis is needed. Here we propose a bilateral connectivity-based neural network for in vivo human esophageal OCT layer segmentation. Our method, connectivity-based CE-Net (Bicon-CE), defines layer segmentation as a combination of pixel connectivity modeling and pixel-wise tissue classification. Bicon-CE outperformed other widely used neural networks and reduced common topological prediction issues in tissues from healthy patients and from patients with Bar rett's esophagus. This is the first end-to-end learning method developed for automatic segmentation of the epithelium in in vivo human esophageal OCT images.

关键词： image processing algorithms image quality Medical image processing Object detection Optical coherence tomography Speckle noise

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Joint artifact correction and super-resolution of image slicing and mapping system via a convolutional neural network

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OPTICS EXPRESS 2021年第5期29卷 7247-7260页

作者： Liu, Anqi Zeng, Xianzi Yuan, Yan Su, Lijuan Wang, Wanyue Beihang Univ Key Lab Precis Optomechatron Technol Minist Educ Beijing 100191 Peoples R China

As the key component of the image mapping spectrometer, the image mapper introduces complex image degradation in the reconstructed images, including low spatial resolution and intensity artifacts. In this paper, we propose a novel image processing method based on the convolutional neural network to perform artifact correction and super-resolution (SR) simultaneously. The proposed joint network contains two branches to handle the artifact correction task and SR task in parallel. The artifact correction module is designed to remove the artifacts in the image and the SR module is used to improve the spatial resolution. An attention fusion module is constructed to combine the features extracted by the artifact correction and SR modules. The fused features are used to reconstruct an artifact-free high-resolution image. We present extensive simulation results to demonstrate that the proposed joint method outperforms state-of-the-art methods and can be generalized to other image mapper designs. We also provide experimental results to prove the efficiency of the joint network. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

关键词： image processing image processing algorithms image quality Neural networks Spatial resolution Spectral imaging

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Automatic traffic monitoring by φ-OTDR data and Hough transform in a real-field environment

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APPLIED OPTICS 2021年第13期60卷 3579-3584页

作者： Catalano, Ester Coscetta, Agnese Cerri, Enis Cennamo, Nunzio Zeni, Luigi Minardo, A. Univ Campania Luigi Vanvitelli Dept Engn Via Roma 29 I-81031 Averse Italy

In this paper, we demonstrate automatic vehicle detection and counting by processing data acquired using a phase-sensitive optical time-domain reflectometer (phi-OTDR) distributed optical fiber sensor. The acquired data are processed using the Hough transform, which detects the lines in the images formed by representing the acquired data in the space-time domain. A rough classification of the vehicles (heavy versus light vehicles) is also proposed, based on the amplitude of the vibration data along the detected lines. The method has been experimentally tested by performing phi-OTDR measurements along a telecommunication fiber cable running in a buried conduit along the state road SS18 (province of Salerno, Italy), opened to normal traffic. Comparison with ground-truth data, manually generated by inspecting video recordings, allowed us to estimate a vehicle detection success rate up to 73%, while heavy vehicles were fully detected. (C) 2021 Optical Society of America

关键词： Amplified spontaneous emission Fiber optic cables image processing algorithms Optical sensing Optical time domain reflectometry Phase retrieval

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Optical Assessment of Tear Glucose by Smart Biosensor Based on Nanoparticle Embedded Contact Lens

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NANO LETTERS 2021年第20期21卷 8933-8940页

作者： Jeon, Hee-Jae Kim, Sooyeon Park, Sijin Jeong, In-Kyung Kang, Jaheon Kim, Young Ro Lee, Dong Yun Chung, Euiheon Gwangju Inst Sci & Technol GIST Dept Biomed Sci & Engn Gwangju 61005 South Korea Purdue Univ Weldon Sch Biomed Engn W Lafayette IN 47907 USA Hanyang Univ Dept Bioengn Coll Engn Seoul 04763 South Korea Hanyang Univ Educ & Res Grp Seoul 04763 South Korea Hanyang Univ Inst Nano Sci & Technol INST Seoul 04763 South Korea Elixir Pharmatech Inc Seoul 04763 South Korea Kyung Hee Univ Kyung Hee Univ Hosp Gangdong Dept Endocrinol & Metab Sch Med Seoul 02447 South Korea Harvard Med Sch Dept Radiol Boston MA 02115 USA Massachusetts Gen Hosp Athinoula A Martinos Ctr Biomed Imaging Charlestown MA 02129 USA GIST AI Grad Sch Gwangju 61005 South Korea GIST Dept Phys & Photon Sci Gwangju 61005 South Korea

Diabetes is a disease condition characterized by a prolonged, high blood glucose level, which may lead to devastating outcomes unless properly managed. Here, we introduce a simple camera-based optical monitoring system (OMS) utilizing the nanoparticle embedded contact lens that produces color changes matching the tear glucose level without any complicated electronic components. Additionally, we propose an image processing algorithm that automatically optimizes the measurement accuracy even in the presence of image blurring, possibly caused by breathing, subtle movements, and eye blinking. As a result, using in vivo mouse models and human tear samples we successfully demonstrated robust correlations across the glucose concentrations measured by three different independent techniques, validating the quantitative efficacy of the proposed OMS. For its methodological simplicity and accessibility, our findings strongly support that the innovation offered by the OMS and processing algorithm would greatly facilitate the glucose monitoring procedure and improve the overall welfare of diabetes patients.

关键词： optical monitoring system (OMS) nanoparticle embedded contact lens (NECLs) image processing algorithms tear glucose

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Periodic poling with a micrometer-range period in thin-film lithium niobate on insulator

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JOURNAL OF THE OPTICAL SOCIETY OF AMERICA B-OPTICAL PHYSICS 2021年第3期38卷 685-691页

作者： Younesi, Mohammadreza Geiss, Reinhard Rajaee, Shakiba Setzpfandt, Frank Chen, Yen-Hung Pertsch, Thomas Friedrich Schiller Univ Jena Abbe Ctr Photon Inst Appl Phys Albert Einstein Str 15 D-07745 Jena Germany Ernst Abbe Hsch Jena Carl Zeiss Promenade 2 D-07745 Jena Germany Natl Cent Univ Dept Opt & Photon Jhongli 320 Taiwan Natl Cent Univ Ctr Astronaut Phys & Engn Jhongli 320 Taiwan Fraunhofer Inst Appl Opt & Precis Engn IOF Ctr Excellence Photon Albert Einstein Str 7 D-07745 Jena Germany

We present our experimental results on electric field poling of X-cut thin-film lithium niobate with poling periods of 1-4 mu m. We used polarization contrast microscopy combined with digital image processing to study the impact of the experimental parameters of the poling process such as electric field strength, poling pulse duration, and layout of metal electrodes on the domain growth and quality of resulting poling patterns. High-quality results with excellent homogeneity of the domain pattern on large areas [i.e., 16 mu m along the domain (z axis) and millimeter long domain gratings along the y axis with a period down to 1 mu m] allow for the integration of numerous devices and structures. (C) 2021 Optical Society of America

关键词： Digital image processing Electron beam lithography image processing algorithms Lithium niobate Phase matching Refractive index

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Deep-learning-based bright-field image generation from a single hologram using an unpaired dataset

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OPTICS LETTERS 2021年第22期46卷 5567-5570页

作者： Terbe, Daniel Orzo, Laszlo Zarandy, Akos Inst Comp Sci & Control H-1111 Budapest Hungary

We adopted an unpaired neural network training technique, namely CycleGAN, to generate bright-field microscope-like images from hologram reconstructions. The motivation for unpaired training in microscope applications is that the construction of paired/parallel datasets is cumbersome or sometimes not even feasible, for example, lensless or flow-through holographic measuring setups. Our results show that the proposed method is applicable in these cases and provides comparable results to the paired training. Furthermore, it has some favorable properties even though its metric scores are lower. The CycleGAN training results in sharper and-from this point of view-more realistic object reconstructions compared to the baseline paired setting. Finally, we show that a lower metric score of the unpaired training does not necessarily imply a worse image generation but a correct object synthesis, yet with a different focal representation. (C) 2021 Optical Society of America

关键词： image processing algorithms image quality image registration Imaging noise Neural networks Phase retrieval

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