80 research outputs found

    Historical map digitization in libraries: Collaborative approaches for large map series

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    Academic libraries are playing a role in the digitization of Canadian government documents, but maps tend to be excluded from these activities due to their unique dimensions and display requirements. Using a topographic map digitization project as a case study, this paper presents a collaborative approach to map scanning, georeferencing, and metadata creation across several Ontario universities. Collectively, the 21 institutions making up the Ontario Council of University Libraries (OCUL) possess and maintain large volumes of Canadian topographic maps. However, few OCUL universities hold complete sets of these map series. While the Canadian government’s most recent topographic maps are now available online, older editions of these maps have not been digitized. This project, currently underway at several participating universities, will enable us to share digital versions of some of our most-requested historical map series with the public at large

    Processing Camera-captured Document Images: Geometric Rectification, Mosaicing, and Layout Structure Recognition

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    This dissertation explores three topics: 1) geometric rectification of cameracaptured document images, 2) camera-captured document mosaicing, and 3) layout structure recognition. The first two topics pertain to camera-based document image analysis, a new trend within the OCR community. Compared to typical scanners,cameras offer convenient, flexible, portable, and non-contact image capture, which enables many new applications and breathes new life into existing ones. The third topic is related to the need for efficient metadata extraction methods, critical for managing digitized documents. The kernel of our geometric rectification framework is a novel method for estimating document shape from a single camera-captured image. Our method uses texture flows detected in printed text areas and is insensitive to occlusion. Classification of planar versus curved documents is done automatically. For planar pages, we obtain full metric rectification. For curved pages, we estimate a planar-strip approximation based on properties of developable surfaces. Our method can process any planar or smoothly curved document captured from an arbitrary position without requiring 3D data, metric data, or camera calibration. For the second topic, we design a novel registration method for document images, which produces good results in difficult situations including large displacements, severe projective distortion, small overlapping areas, and lack of distinguishable feature points. We implement a selective image composition method that outperforms conventional image blending methods in overlapping areas. It eliminates double images caused by mis-registration and preserves the sharpness in overlapping areas. We solve the third topic with a graph-based model matching framework. Layout structures are modeled by graphs, which integrate local and global features and are extensible to new features in the future. Our model can handle large variation within a class and subtle differences between classes. Through graph matching, the layout structure of a document is discovered. Our layout structure recognition technique accomplishes document classification and logical component labeling at the same time. Our model learning method enables a model to adapt to changes in classes over time

    System Design Considerations for a Low-Intensity Hyperspectral Imager of Sensitive Cultural Heritage Manuscripts

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    Cultural heritage imaging is becoming more common with the increased availability of more complex imaging systems, including multi- and hyperspectral imaging (MSI and HSI) systems. A particular concern with HSI systems is the broadband source required, regularly including infrared and ultraviolet spectra, which may cause fading or damage to a target. Guidelines for illumination of such objects, even while on display at a museum, vary widely from one another. Standards must be followed to assure the curator to allow imaging and ensure protection of the document. Building trust in the cultural heritage community is key to gaining access to objects of significant import, thus allowing scientists, historians, and the public to view digitally preserved representations of the object, and to allow further discovery of the object through spectral processing and analysis. Imaging was conducted with a light level of 270 lux at variable ground sample distances (GSD’s). The light level was chosen to maintain a total dose similar to an hour’s display time at a museum, based on the United Kingdom standard for cultural heritage display, PAS 198:2012. The varying GSD was used as a variable to increase signal-to-noise ratios (SNR) or decrease total illumination time on a target. This adjustment was performed both digitally and physically, and typically results in a decrease in image quality, as the spatial resolution of the image decreases. However, a technique called “panchromatic sharpening” was used to recover some of the spatial resolution. This method fuses a panchromatic image with good spatial resolution with a spectral image (either MSI or HSI) with poorer spatial resolution to construct a derivative spectral image with improved spatial resolution. Detector systems and additional methods of data capture to assist in processing of cultural heritage documents are investigated, with specific focus on preserving the physical condition of the potentially sensitive documents

    Motion compensated iterative reconstruction for cardiac X-ray tomography

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    Within this Ph.D. project, three-dimensional reconstruction methods for moving objects (with a focus on the human heart) from cone-beam X-ray projections using iterative reconstruction algorithms were developed and evaluated. This project was carried in collaboration with the Digital Imaging Group of Philips Research Europe – Hamburg. In cardiac cone-beam computed tomography (CT) a large effort is continuously dedicated to increase scanning speed in order to minimize patient or organ motion during acquisition. In particular, motion causes severe artifacts such as blurring and streaks in tomographic images. While for a large class of applications the current scanning speed is sufficient, in cardiac CT image reconstruction improvements are still required. Whereas it is currently feasible to achieve stable image quality in the resting phases of the cardiac cycle, in the phase of fast motion data acquisition is too slow. A variety of algorithms to reduce or compensate for motion artifacts have been proposed in literature. Most of the correction methods address the calculation of consistent projection data belonging to the same motion state (gated CT reconstruction). Even if gated CT leads to better results, not only with respect to the processing time but also regarding the image quality, it is also limited in its temporal and spatial resolution due to the mechanical movement of the gantry. This can lead to motion blurring, especially in the phases of fast cardiac motion during the RR interval. A motion-compensated reconstruction method for CT can be used to improve the resolution of the reconstructed image and to suppress motion blurring. Iterative techniques are a promising approach to solve this problem, since no direct inversion methods are known for arbitrarily moving objects. In this work, we therefore introduced motion compensation into image reconstruction. In order to determine the unknown cardiac motion, 3 different cardiac-motion estimation methodologies were implemented. Visual and quantitative assessment of the method in a number of applications, including: phantoms; cardiac CT reconstructions; Region of Interest (ROI) CT reconstructions of left and right coronaries of several clinical patients, confirmed its potential

    Markerless 3D Head Tracking for Motion Correction in High Resolution PET Brain Imaging

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    Modeling Ozark Caves with Structure-from-Motion Photogrammetry: An Assessment of Stand-Alone Photogrammetry for 3-Dimensional Cave Survey

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    Nearly all aspects of karst science and management begin with a map. Yet despite this fact, cave survey is largely conducted in the same archaic way that is has been for years - with a compass, tape measure, and a sketchpad. Traditional cave survey can establish accurate survey lines quickly. However, passage walls, ledges, profiles, and cross-sections are time intensive and ultimately rely on the sketcher’s experience at interpretively hand drawing these features between survey stations. This project endeavors to experiment with photogrammetry as a method of improving on traditional cave survey, while also avoiding some of the major pitfalls of terrestrial laser scanning. The proposed method allows for the creation of 3D models which capture cave wall geometry, important cave formations, as well as providing the ability to create cross sections anywhere desired. The interactive 3D cave models are produced cheaply, with equipment that can be operated in extremely confined, harsh conditions, by unpaid volunteers with little to no technical training. While the rapid advancement of photogrammetric software has led to its use in many 3D modeling applications, there is only a sparse body of research examining the use of photogrammetry as a standalone method for surveying caves. The proposed methodology uses a GoPro camera and a 1000 lumen portable floodlight to capture still images down the length of cave passages. The procedure goes against several traditional rules of thumb, both operating in the dark with a moving light source, as well as utilizing a wide angle, fish eye lens, to capture scene information that is not perpendicular to the camera\u27s field of view. Images are later processed into 3D models using Agisoft’s PhotoScan. Four caves were modeled using the method, with varying levels of success. The best results occurred in dry confined passages, while passages greater than 9 meters (30ft) in width, or those with a great deal of standing water in the floor, produced large holes. An additional experiment occurred in the University of Arkansas utility tunnel

    3D high resolution techniques applied on small and medium size objects: from the analysis of the process towards quality assessment

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    The need for metric data acquisition is an issue strictly related to the human capability of describing the world with rigorous and repeatable methods. From the invention of photography to the development of advanced computers, the metric data acquisition has been subjected to rapid mutation, and nowadays there exists a strict connection between metric data acquisition and image processing, Computer Vision and Artificial Intelligence. The sensor devices for the 3D model generation are various and characterized by different functioning principles. In this work, optical passive and active sensors are treated, focusing specifically on close-range photogrammetry, Time of Flight (ToF) sensors and Structured-light scanners (SLS). Starting from the functioning principles of the techniques and showing some issues related to them, the work highlights their potentialities, analyzing the fundamental and most critical steps of the process leading to the quality assessment of the data. Central themes are the instruments calibration, the acquisition plan and the interpretation of the final results. The capability of the acquisition techniques to satisfy unconventional requirements in the field of Cultural Heritage is also shown. The thesis starts with an overview about the history and developments of 3D metric data acquisition. Chapter 1 treats the Human Vision System and presents a complete overview of 3D sensing devices. Chapter 2 starts from the enunciation of the basic principle of close-range photogrammetry considering digital cameras functioning principles, calibration issues, and the process leading to the 3D mesh reconstruction. The case of multi-image acquisition is analyzed, deepening the quality assessment of the photogrammetric process through a case study. Chapter 3 is devoted to the range-based acquisition techniques, namely ToF laser scanners and SLSs. Lastly, Chapter 4 focuses on unconventional applications of the mentioned high-resolution acquisition techniques showing some examples of study cases in the field of Cultural Heritage
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