Relevant bibliographies by topics / Adaptive imaging system

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Adaptive imaging system'

Author: Grafiati
Published: 25 January 2025

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Journal articles on the topic "Adaptive imaging system"

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Rigby, Kenneth Wayne. "Adaptive ultrasound imaging system." Journal of the Acoustical Society of America 121, no. 5 (2007): 2495. http://dx.doi.org/10.1121/1.2739204.

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Larichev, A. V., P. V. Ivanov, N. G. Iroshnikov, V. I. Shmalgauzen, and L. J. Otten. "Adaptive system for eye-fundus imaging." Quantum Electronics 32, no. 10 (October 31, 2002): 902–8. http://dx.doi.org/10.1070/qe2002v032n10abeh002314.

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Choi, Junoh. "Iris imaging system with adaptive optical elements." Journal of Electronic Imaging 21, no. 1 (February 27, 2012): 013004. http://dx.doi.org/10.1117/1.jei.21.1.013004.

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Griffiths, J. A., M. G. Metaxas, S. Pani, H. Schulerud, C. Esbrand, G. J. Royle, B. Price, et al. "Preliminary images from an adaptive imaging system." Physica Medica 24, no. 2 (June 2008): 117–21. http://dx.doi.org/10.1016/j.ejmp.2008.01.003.

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Kaltiokallio, Ossi, Riku Jantti, and Neal Patwari. "ARTI: An Adaptive Radio Tomographic Imaging System." IEEE Transactions on Vehicular Technology 66, no. 8 (August 2017): 7302–16. http://dx.doi.org/10.1109/tvt.2017.2664938.

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Simopoulos, Constantine, and Bhaskar Ramamurthy. "Ultrasound imaging system having motion adaptive gain." Journal of the Acoustical Society of America 128, no. 1 (2010): 517. http://dx.doi.org/10.1121/1.3472340.

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Gao Meijing, 高美静, 顾海华 Gu Haihua, 关丛荣 Guan Congrong, and 吴伟龙 Wu Weilong. "Adaptive Position Calibration for Thermal Microscopic Imaging System." Acta Optica Sinica 33, no. 1 (2013): 0111002. http://dx.doi.org/10.3788/aos201333.0111002.

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Wu Chuhan, 武楚晗, 张晓芳 Zhang Xiaofang, 陈蔚林 Chen Weilin, and 常军 Chang Jun. "Fundus Imaging System Based on Tomographic Adaptive Optics." Acta Optica Sinica 37, no. 4 (2017): 0411002. http://dx.doi.org/10.3788/aos201737.0411002.

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Smith, Stephen W., and Gregg E. Trahey. "High speed adaptive ultrasonic phased array imaging system." Journal of the Acoustical Society of America 87, no. 6 (June 1990): 2806. http://dx.doi.org/10.1121/1.398978.

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Bille, Josef F., Mikael Agopov, Cristina Alvarez-diez, Meng Han, Nina Korablinova, Ulrich von Pape, Olivier La Schiazza, Melanie Schwingel, Hongwei Zhang, and Frank Müller. "Compact adaptive optics system for multiphoton fundus imaging." Journal of Modern Optics 55, no. 4-5 (February 20, 2008): 749–58. http://dx.doi.org/10.1080/09500340701608024.

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Dissertations / Theses on the topic "Adaptive imaging system"

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Fu, Bo. "A configurable real-time adaptive imaging and illumination system." Thesis, University of Nottingham, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.582595.

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Research on information processing in neuronal networks may lead to a better understanding of many brain diseases and disorders and could inform potential future treatments. It may also lead to the development of more intelligent electronic technology. To understand how the brain processes information we need to study the patterns of action potentials (APs) in a neuronal network over the long-term. The aim of this project, therefore, is to develop an optical system to both detect and stimulate APs in a small neuronal network. A closed-loop system has been developed that consists of a signal detection tool (a camera system), a signal analysis tool (a real-time computer) and a signal delivery tool (a spatially modulated light source). The conventional techniques for measuring APs, using patch clamp electrodes or multi electrode arrays for example, are limited by the spatial extent, or the spatial resolution, that can be achieved. Alternatively, optical imaging systems can be used to monitor APs. Imaging systems can achieve high-resolution across a wide field-of-view. To record network-wide neuronal activity a high- speed camera is necessary. Ideally imaging needs to be performed continuously over long periods of time. However, continuous high-speed imaging is typically not possible using commercially available systems due to restrictions in bandwidth.
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Panayiotou, Stephen. "A domain independent adaptive imaging system for visual inspection." Thesis, University of Greenwich, 1995. http://gala.gre.ac.uk/8696/.

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Computer vision is a rapidly growing area. The range of applications is increasing very quickly, robotics, inspection, medicine, physics and document processing are all computer vision applications still in their infancy. All these applications are written with a specific task in mind and do not perform well unless there under a controlled environment. They do not deploy any knowledge to produce a meaningful description of the scene, or indeed aid in the analysis of the image. The construction of a symbolic description of a scene from a digitised image is a difficult problem. A symbolic interpretation of an image can be viewed as a mapping from the image pixels to an identification of the semantically relevant objects. Before symbolic reasoning can take place image processing and segmentation routines must produce the relevant information. This part of the imaging system inherently introduces many errors. The aim of this project is to reduce the error rate produced by such algorithms and make them adaptable to change in the manufacturing process. Thus a prior knowledge is needed about the image and the objects they contain as well as knowledge about how the image was acquired from the scene (image geometry, quality, object decomposition, lighting conditions etc,). Knowledge on algorithms must also be acquired. Such knowledge is collected by studying the algorithms and deciding in which areas of image analysis they work well in. In most existing image analysis systems, knowledge of this kind is implicitly embedded into the algorithms employed in the system. Such an approach assumes that all these parameters are invariant. However, in complex applications this may not be the case, so that adjustment must be made from time to time to ensure a satisfactory performance of the system. A system that allows for such adjustments to be made, must comprise the explicit representation of the knowledge utilised in the image analysis procedure. In addition to the use of a priori knowledge, rules are employed to improve the performance of the image processing and segmentation algorithms. These rules considerably enhance the correctness of the segmentation process. The most frequently given goal, if not the only one in industrial image analysis is to detect and locate objects of a given type in the image. That is, an image may contain objects of different types, and the goal is to identify parts of the image. The system developed here is driven by these goals, and thus by teaching the system a new object or fault in an object the system may adapt the algorithms to detect these new objects as well compromise for changes in the environment such as a change in lighting conditions. We have called this system the Visual Planner, this is due to the fact that we use techniques based on planning to achieve a given goal. As the Visual Planner learns the specific domain it is working in, appropriate algorithms are selected to segment the object. This makes the system domain independent, because different algorithms may be selected for different applications and objects under different environmental condition.
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Trumbull, Tara. "Simulation and Analysis of an Adaptive SPECT Imaging System for Tumor Estimation." Thesis, The University of Arizona, 2011. http://hdl.handle.net/10150/144580.

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We have developed a simulation of the AdaptiSPECT small-animal Single Photon Emission Computed Tomography (SPECT) imaging system. The simulation system is entitled SimAdaptiSPECT and is written in C, NVIDIA CUDA, and Matlab. Using this simulation, we have accomplished an analysis of the Scanning Linear Estimation (SLE) technique for estimating tumor parameters, and calculated sensitivity information for AdaptiSPECT configurations.SimAdaptiSPECT takes, as input, simulated mouse phantoms (generated by MOBY) contained in binary files and AdaptiSPECT configuration geometry contained in ASCII text files. SimAdaptiSPECT utilizes GPU parallel processing to simulate AdaptiSPECT images. SimAdaptiSPECT also utilizes GPU parallel processing to perform 3-D image reconstruction from 2-D AdaptiSPECT camera images (real or simulated), using a novel variant of the Ordered Subsets Expectation Maximization (OSEM) algorithm. Methods for generating the inputs, such as a population of randomly varying numerical mouse phantoms with randomly varying hepatic lesions, are also discussed.
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Chan, Lok-sang, and 陳樂生. "Adaptive flow detector and estimator for ultrasound high frame rate vector flow imaging." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B47753043.

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Cardiovascular diseases is a leading cause of death worldwide and improvement of the corresponding screening tool is the best way to deal with this clinical problem. In this thesis we attempted to develop a framework of ultrasound high frame rate vector flow imaging (VFI) by emphasizing on the design of corresponding flow detector and flow estimator. We believe that the high temporal resolution and the complex blood flow visualization ability of high frame rate VFI enables it to be further developed as a reliable flow imaging modality for cardiological examination. In order to achieve high temporal resolution, fast data acquisition algorithm was applied in the framework. Doppler signals acquired using this acquisition algorithm have two unique characteristics comparing with conventional data acquisition algorithm: (1) widen spectral bandwidth and (2) greater clutter to blood signal ratio. These signal characteristics give rise to unique signal processing. In addition, complex blood flow pattern, which is common in cardiological examination, induces extra challenges in implementing high frame rate VFI. In this thesis, flow detector which is adaptive to different flow scenarios and high dynamic range 2D flow estimator were presented. The proposed flow detector employes K-means++ clustering algorithm to classify clutter components from acquired Doppler signals. As a performance analysis, Field II simulation studies were performed by a parabolic flow phantom (flow velocity: 10mm/s to 200mm/s; tissue motion: 10mm/s; beam-flow angle: 60?). The post-filtered Doppler power map and BCR were used as qualitative and quantitativemeasures of detectors performance. Analyzed result has indicated that, as compared with clutter downmixing detector and eigen-based detector, the proposed flow detector could classify and suppress clutter component more effectively. Results also suggested that the proposed flow detector is more adaptive to slow flow scenarios where existing flow detectors failed to distinguish between blood and clutter components. For the proposed flow estimator, it was characterized by the interpolation of speckle tracking results in Lagrangian reference frame. The estimation bias and RMS error were calculated for different flow scenarios (flow velocity: 100mm/s to 500mm/s; beam-flow angle: 15? to 60?). It was found that the proposed flow estimator provides higher dynamic range than conventional speckle tracking-based flow estimator. Nonetheless, it is also observed that the estimation variances and errors increases in slow flow scenarios. In order to demonstrate the medical potential of the proposed high frame rate VFI framework. A carotid bifurcation simulation model with realistic blood flow pattern calculated using computational fluid dynamic software was applied in the performance evaluation study. In the VFI image obtained, complex blood flow pattern was readily visualized. In contrast, conventional ultrasound flow imaging was only able to estimate axial velocity map and thus lead to many ambiguities in analyzing the complex blood flow pattern. It proved that ultrasound high frame rate VFI has the potential to be further developed into a new cardiological examination technique.
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Electrical and Electronic Engineering
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Pazder, John Stanley. "The optical design of an adaptive optics system imaging two selectable atmospheric layers." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ32673.pdf.

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Elgort, Daniel Robert. "Real-Time Catheter Tracking and Adaptive Imaging for Interventional Cardiovascular MRI." Case Western Reserve University School of Graduate Studies / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=case1111437062.

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Bai, Yu. "Characterization of an Adaptive Optics System for Vision Studies." University of Dayton / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1461796856.

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Kasper, Markus Erdmann. "Optimization of an adaptive optics system and its application to high-resolution imaging spectroscopy of T Tauri." [S.l. : s.n.], 2000. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB8986347.

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Almotiri, Jasem. "A Multi-Anatomical Retinal Structure Segmentation System for Automatic Eye Screening Using Morphological Adaptive Fuzzy Thresholding." Thesis, University of Bridgeport, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10975223.

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Eye exam can be as efficacious as physical one in determining health concerns. Retina screening can be the very first clue to detecting a variety of hidden health issues including pre-diabetes and diabetes. Through the process of clinical diagnosis and prognosis; ophthalmologists rely heavily on the binary segmented version of retina fundus image; where the accuracy of segmented vessels, optic disc and abnormal lesions extremely affects the diagnosis accuracy which in turn affect the subsequent clinical treatment steps. This thesis proposes an automated retinal fundus image segmentation system composed of three segmentation subsystems follow same core segmentation algorithm. Despite of broad difference in features and characteristics; retinal vessels, optic disc and exudate lesions are extracted by each subsystem without the need for texture analysis or synthesis. For sake of compact diagnosis and complete clinical insight, our proposed system can detect these anatomical structures in one session with high accuracy even in pathological retina images.

The proposed system uses a robust hybrid segmentation algorithm combines adaptive fuzzy thresholding and mathematical morphology. The proposed system is validated using four benchmark datasets: DRIVE and STARE (vessels), DRISHTI-GS (optic disc), and DIARETDB1 (exudates lesions). Competitive segmentation performance is achieved, outperforming a variety of up-to-date systems and demonstrating the capacity to deal with other heterogenous anatomical structures.

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Namroud, Iman. "An Analysis of Aliasing and Image Restoration Performance for Digital Imaging Systems." University of Dayton / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1399046084.

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Books on the topic "Adaptive imaging system"

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Byron, Welsh, ed. Imaging through turbulence. Boca Raton: CRC Press, 1996.

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Tyson, Robert K. Lighter side of adaptive optics. Belingham, Wash: SPIE, 2009.

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United States. National Aeronautics and Space Administration., ed. Data compression using adaptive transform coding. [Washington, DC: National Aeronautics and Space Administration, 1988.

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Roddier, Franois. Adaptive Optics in Astronomy. Cambridge: Cambridge University Press, 1999.

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N, Ageorges, Dainty J. C, North Atlantic Treaty Organization. Scientific Affairs Division., and NATO Advanced Study Institute on Laser Guide Star Adaptive Optics for Astronomy (1997 : Cargèse, France), eds. Laser guide star adaptive optics for astronomy. Dordrecht: Kluwer Academic Publishers, 2000.

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Paul, Casasent David, Clark Timothy S, and SPIE (Society), eds. Adaptive coded aperture imaging and non-imaging sensors: 29-30 August 2007, San Diego, California, USA. Bellingham, Wash: SPIE, 2007.

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1970-, Urey Hakan, Society of Photo-optical Instrumentation Engineers., Semiconductor Equipment and Materials International., Solid State Technology (Organization), and Sandia National Laboratories, eds. MOEMS display and imaging systems: 28-29 January 2003, San Jose, California, USA. Bellingham, Wash., USA: SPIE, 2003.

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Rogers, Stanley. Adaptive coded aperture imaging, non-imaging, and unconventional imaging sensor systems II: 1-2 August 2010, San Diego, California, United States. Bellingham, Wash: SPIE, 2010.

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1970-, Urey Hakan, Dickensheets David L, Society of Photo-optical Instrumentation Engineers., Semiconductor Equipment and Materials International., Solid State Technology (Organization), and Sandia National Laboratories, eds. MOEMS display and imaging systems III: 24-25 January 2005, San Jose, California, USA. Bellingham, Wash., USA: SPIE, 2005.

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1970-, Urey Hakan, Dickensheets David L, and Society of Photo-optical Instrumentation Engineers., eds. MOEMS display and imaging systems II: 26-27 January 2004, San Jose, California, USA. Bellingham, Wash., USA: SPIE, 2004.

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Book chapters on the topic "Adaptive imaging system"

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Nakazaki, Keiichiro, Yuri Murakami, and Masahiro Yamaguchi. "Hybrid-Resolution Spectral Imaging System Using Adaptive Regression-Based Reconstruction." In Lecture Notes in Computer Science, 142–50. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07998-1_17.

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Kissler-Patig, M., M. Casali, B. Delabre, N. Hubin, H. U. Käufl, P. Jolley, M. Le Louarn, S. Oberti, and J. Pirard. "CASIS: Cassegrain Adaptive-Optics Simultaneous Imaging System for the VLT." In Astrophysics and Space Science Proceedings, 475–79. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-1-4020-9190-2_85.

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Shirai, Tomohiro, and T. M. Barnes. "Partially coherent imaging through turbulence with an all-optical adaptive-optics system." In Coherence and Quantum Optics VIII, 395–96. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4419-8907-9_86.

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Tyler, David W., and Gary C. Loos. "Simulation study of a low-light-level wavefront sensor driving a low-order, near-IR adaptive optics system." In Very High Angular Resolution Imaging, 308–10. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0880-5_54.

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Kavak, Ayse Gulbin. "The Future of Radiotherapy: Integrating Pet Imaging with Biology-Guided Radiation Therapy." In The Latest Innovative Approaches in Radiation Therapy, 27–45. Istanbul: Nobel Tip Kitabevleri, 2024. http://dx.doi.org/10.69860/nobel.9786053359425.2.

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Biology-guided radiation therapy (BgRT) is a significant therapy method in radiotherapy (RT) that enhances treatment precision and effectiveness by utilizing biological markers. Traditional RT methods, using high-energy radiation to destroy cancer cells, have evolved through technological advancements such as linear accelerator (Linac) systems and imaging techniques. Intensity-Modulated Radiotherapy (IMRT) and Stereotactic Body Radiotherapy (SBRT) have improved targeting and reduced damage to healthy tissues. However, conventional RT has some challenges in treating multiple tumors simultaneously, particularly in metastatic cancer. BgRT addresses these limitations by incorporating Positron Emission Tomography (PET) to guide radiation based on real-time biological activity. This approach allows for personalized treatment plans tailored to the genetic and molecular profiles of tumors, enhancing treatment effectiveness and minimizing side effects. BgRT’s ability to monitor tumors dynamically during treatment enables immediate adjustments, optimizing therapeutic outcomes. BgRT machine system, an FDA-approved device for IMRT, SABR, and BgRT technology by integrating PET imaging with radiation delivery. Quality assurance studies have demonstrated the system’s dosimetric precision and imaging accuracy, supporting its clinical efficacy. BgRT is particularly promising for treating oligometastatic and polymetastatic diseases, offering precise, personalized therapies that target multiple tumors in a single session. Future advancements in imaging techniques, PET tracers, and adaptive radiotherapy systems are expected to further enhance BgRT’s capabilities. Continuous research and development in this field are crucial for improving cancer treatment outcomes and expanding the therapeutic options available in radiation oncology.
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Langlois, M., D. Sandler, and D. McCarthy. "Large Ground-Based Telescopes with High Order Adaptive Optics for Imaging Faint Objects and Extra-Solar Planets." In Planets Outside the Solar System: Theory and Observations, 297–306. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-011-4623-4_19.

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Steinberg, Bernard D. "Self-Cohering a Large, Distorted Antenna for Microwave Imaging." In Adaptive and Learning Systems, 165–73. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4757-1895-9_11.

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Harris, J. G., and Yu-Ming Chiang. "Nonuniformity Correction of Imaging Arrays Using the Constant Statistics Constraint." In Smart Adaptive Systems on Silicon, 269–84. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4020-2782-6_16.

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Cook, Stephen P. "Imagining a Theory of Everything for Adaptive Systems." In Cellular Origin, Life in Extreme Habitats and Astrobiology, 623–38. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4156-0_33.

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Izzetoglu, Kurtulus, Hasan Ayaz, Justin Menda, Meltem Izzetoglu, Anna Merzagora, Patricia A. Shewokis, Kambiz Pourrezaei, and Banu Onaral. "Applications of Functional Near Infrared Imaging: Case Study on UAV Ground Controller." In Foundations of Augmented Cognition. Directing the Future of Adaptive Systems, 608–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21852-1_70.

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Conference papers on the topic "Adaptive imaging system"

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Payeur, Nicolas, Koichi Watanabe-Brouillette, Ophélie Légaré, Valentina Pieters, Émile Tremblay-Antoine, Philippe Truchon, Antoine Veillette, et al. "Realizations and future projects of the high contrast imaging balloon system (HiCIBaS) platform." In Adaptive Optics Systems IX, edited by Dirk Schmidt, Elise Vernet, and Kathryn J. Jackson, 302. SPIE, 2024. http://dx.doi.org/10.1117/12.3019172.

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Qiu, Frank, Josh Michalenko, Lilian K. Casias, Cameron J. Radosevich, Jon Slater, and Eric A. Shields. "Characterization of point-source transient events with a rolling-shutter compressed sensing system." In Unconventional Imaging, Sensing, and Adaptive Optics 2024, edited by Santasri R. Bose-Pillai, Jean J. Dolne, and Matthew Kalensky, 76. SPIE, 2024. http://dx.doi.org/10.1117/12.3028690.

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Wang, Ao, Chunyuan Gan, Haocheng Han, Hongyi Xiong, Jiawei Zhao, Chutian Wang, and Lin Feng. "Dynamic Adaptive Imaging System on Optoelectronic Tweezers Platform." In 2024 IEEE International Conference on Robotics and Automation (ICRA), 15622–27. IEEE, 2024. http://dx.doi.org/10.1109/icra57147.2024.10611608.

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Burns, Stephen A., W. Zou, Z. Zhong, G. Huang, and X. Qi. "AO system considerations for Retinal Imaging." In Adaptive Optics: Methods, Analysis and Applications. Washington, D.C.: OSA, 2011. http://dx.doi.org/10.1364/aopt.2011.ama1.

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Wang, Feiling, and Christopher Spivey. "Auto-focus Like Adaptive Optics Imaging System." In Adaptive Optics: Analysis, Methods & Systems. Washington, D.C.: OSA, 2015. http://dx.doi.org/10.1364/aoms.2015.aom4b.4.

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Morossi, C., M. Franchini, R. Ragazzoni, G. Sedmak, A. Suzuki, J. Albetski, J. Africano, D. Nishimoto, and S. Restaino. "Compensated Imaging System (CIS) Observations of the Circumstellar Envelope of P-Cygni." In Adaptive Optics. Washington, D.C.: Optica Publishing Group, 1995. http://dx.doi.org/10.1364/adop.1995.wa3.

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This project is a direct result from OSA and the ESO's first adaptive optics conference. The objective for the Air Force Maui Optical Station (AMOS) was to collaborate and present to the astronomical community the benefits and advantages of using an adaptive optics system for astronomical imaging research.
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Li, Jin, Jari Koivusaari, Jarmo Takala, Moncef Gabbouj, and Hexin Chen. "Human visual system based adaptive inter quantization." In Electronic Imaging 2008, edited by Reiner Creutzburg and Jarmo H. Takala. SPIE, 2008. http://dx.doi.org/10.1117/12.765045.

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Qiao, Lintian, and Klara Nahrstedt. "Lip synchronization within an adaptive VOD system." In Electronic Imaging '97, edited by Martin Freeman, Paul Jardetzky, and Harrick M. Vin. SPIE, 1997. http://dx.doi.org/10.1117/12.264290.

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Albetski, John P. "History of the AMOS 1.6m Telescope Compensated Imaging System." In Adaptive Optics for Large Telescopes. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/aolt.1992.awc4.

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The AMOS Compensated Imaging System (CIS) was developed during the mid and late 1970’s by the Defense Advanced Research Projects Agency. Upon installation on the AMOS 1.6 meter telescope in March of 1982 it became the first compensated imaging system to be used on a large aperture telescope. Today the CIS continues to operate as a primary AMOS sensor system and is used to collect imagery of space objects on a nightly basis. Now that many large aperture astronomical telescopes are being equipped with adaptive optics, it is appropriate that we review the design of and experience with this system and the lessons learned from its operation over a period of more than ten years.
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Ficocelli, Maurizio, and Foued Ben Amara. "Control System Design for Retinal Imaging Adaptive Optics Systems." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-81800.

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This paper presents a solution to control system design issues for adaptive optics systems used in retinal imaging. In this paper, the control problem for adaptive optics systems is generalized to that of shape control for a flexible membrane representing a deformable membrane mirror. Due to the dynamic nature of the aberrations in the eye, the shape control problem addressed is the tracking of an unknown and time-varying shape for a distributed membrane (i.e., desired shape of the mirror). The design of a controller to achieve the shape control objective is based on a model of a distributed parameter system representing the mirror membrane. To accomplish this task, a multivariable centralized controller is utilized. Since the desired shape of the mirror is unknown and time-varying, the controller is tuned online to converge to the controller needed to achieve regulation. This is done iteratively, by taking advantage of the Q-parameterization of all stabilizing controllers, so that the controller will converge to the ideal controller. The online tuning is used to compensate for the lack of information of the desired shape for the deformable mirror.
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Reports on the topic "Adaptive imaging system"

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Searcy, Stephen W., and Kalman Peleg. Adaptive Sorting of Fresh Produce. United States Department of Agriculture, August 1993. http://dx.doi.org/10.32747/1993.7568747.bard.

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This project includes two main parts: Development of a “Selective Wavelength Imaging Sensor” and an “Adaptive Classifiery System” for adaptive imaging and sorting of agricultural products respectively. Three different technologies were investigated for building a selectable wavelength imaging sensor: diffraction gratings, tunable filters and linear variable filters. Each technology was analyzed and evaluated as the basis for implementing the adaptive sensor. Acousto optic tunable filters were found to be most suitable for the selective wavelength imaging sensor. Consequently, a selectable wavelength imaging sensor was constructed and tested using the selected technology. The sensor was tested and algorithms for multispectral image acquisition were developed. A high speed inspection system for fresh-market carrots was built and tested. It was shown that a combination of efficient parallel processing of a DSP and a PC based host CPU in conjunction with a hierarchical classification system, yielded an inspection system capable of handling 2 carrots per second with a classification accuracy of more than 90%. The adaptive sorting technique was extensively investigated and conclusively demonstrated to reduce misclassification rates in comparison to conventional non-adaptive sorting. The adaptive classifier algorithm was modeled and reduced to a series of modules that can be added to any existing produce sorting machine. A simulation of the entire process was created in Matlab using a graphical user interface technique to promote the accessibility of the difficult theoretical subjects. Typical Grade classifiers based on k-Nearest Neighbor techniques and linear discriminants were implemented. The sample histogram, estimating the cumulative distribution function (CDF), was chosen as a characterizing feature of prototype populations, whereby the Kolmogorov-Smirnov statistic was employed as a population classifier. Simulations were run on artificial data with two-dimensions, four populations and three classes. A quantitative analysis of the adaptive classifier's dependence on population separation, training set size, and stack length determined optimal values for the different parameters involved. The technique was also applied to a real produce sorting problem, e.g. an automatic machine for sorting dates by machine vision in an Israeli date packinghouse. Extensive simulations were run on actual sorting data of dates collected over a 4 month period. In all cases, the results showed a clear reduction in classification error by using the adaptive technique versus non-adaptive sorting.
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2

Svedeman. L51729 Gas Scrubber Performance Evaluation - Measurement Methods. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), April 1995. http://dx.doi.org/10.55274/r0010420.

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Scrubbers and separators are used in natural gas pipelines to remove solid and liquid materials from the gas stream. Failure to remove the entrained materials from the gas can result in equipment damage, increased pressure drop due to liquid accumulation, flow measurement errors, and corrosion. The performance of separators is rarely tested after a separator is installed because there is a lack of test instrumentation and it is difficult to conduct tests at the high pressures. The only indicators of poor separator performance are recurring problems in downstream equipment or the detection of accumulated materials in downstream piping. Instrumentation is needed that can verify separator performance when the unit is installed and to periodically monitor separator performance. The report documents results of instrument tests. The objectives of the instrument evaluations were to verify that the instruments could be used to measure particles penetrating a separator, to provide a comparative evaluation of the instruments, and to identify any measurement problems that could be encountered in field testing. One important result was that the separator minimum removable drop size increased as the operating pressure increased. This trend is not generally known, since there is a lack of test results for pressures above atmospheric pressure. The separator performance test results are documented in this report. Two different particle measuring instruments were evaluated for documenting separator performance. The two instruments were the video imaging system with automatic image analysis and the laser-based phase Doppler particle measuring system. The instruments were evaluated in laboratory tests that were conducted on a commercially available vane-type separator. The objectives of the instrument evaluations were to verify that the instruments could be used to measure particles penetrating a separator, to provide a comparative evaluation of the two instruments, and to identify any measurement problems that could be encountered in field testing. The video imaging system has a number of attractive attributes, but it was not able to measure the small diameter drops at the separator exit. The primary limitation was that the optical system could not clearly image the small drops (in the range from 5 to 30 um). The phase Doppler particle measuring system was capable of measuring all of the parameters needed to document the separator performance. Based on the instrument evaluations, future efforts on developing measurement methods for documenting separator performance should focus on adapting the phase Doppler system to field testing.
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