1,725 research outputs found
Deep Unrestricted Document Image Rectification
In recent years, tremendous efforts have been made on document image
rectification, but existing advanced algorithms are limited to processing
restricted document images, i.e., the input images must incorporate a complete
document. Once the captured image merely involves a local text region, its
rectification quality is degraded and unsatisfactory. Our previously proposed
DocTr, a transformer-assisted network for document image rectification, also
suffers from this limitation. In this work, we present DocTr++, a novel unified
framework for document image rectification, without any restrictions on the
input distorted images. Our major technical improvements can be concluded in
three aspects. Firstly, we upgrade the original architecture by adopting a
hierarchical encoder-decoder structure for multi-scale representation
extraction and parsing. Secondly, we reformulate the pixel-wise mapping
relationship between the unrestricted distorted document images and the
distortion-free counterparts. The obtained data is used to train our DocTr++
for unrestricted document image rectification. Thirdly, we contribute a
real-world test set and metrics applicable for evaluating the rectification
quality. To our best knowledge, this is the first learning-based method for the
rectification of unrestricted document images. Extensive experiments are
conducted, and the results demonstrate the effectiveness and superiority of our
method. We hope our DocTr++ will serve as a strong baseline for generic
document image rectification, prompting the further advancement and application
of learning-based algorithms. The source code and the proposed dataset are
publicly available at https://github.com/fh2019ustc/DocTr-Plus
Document image restoration - For document images scanned from bound volumes -
Ph.DDOCTOR OF PHILOSOPH
Computer Assisted Relief Generation - a Survey
In this paper we present an overview of the achievements accomplished to date in the field of computer aided relief
generation. We delineate the problem, classify the different solutions, analyze similarities, investigate the evelopment and review the approaches according to their particular relative strengths and weaknesses. In consequence this survey is likewise addressed to researchers and artists through providing valuable insights into the theory behind the different concepts in this field and augmenting the options available among the methods presented with regard to practical application
3D MODELLING AND RAPID PROTOTYPING FOR CARDIOVASCULAR SURGICAL PLANNING – TWO CASE STUDIES
In the last years, cardiovascular diagnosis, surgical planning and intervention have taken advantages from 3D modelling and rapid
prototyping techniques. The starting data for the whole process is represented by medical imagery, in particular, but not exclusively,
computed tomography (CT) or multi-slice CT (MCT) and magnetic resonance imaging (MRI). On the medical imagery, regions of
interest, i.e. heart chambers, valves, aorta, coronary vessels, etc., are segmented and converted into 3D models, which can be finally
converted in physical replicas through 3D printing procedure. In this work, an overview on modern approaches for automatic and semiautomatic
segmentation of medical imagery for 3D surface model generation is provided. The issue of accuracy check of surface
models is also addressed, together with the critical aspects of converting digital models into physical replicas through 3D printing
techniques. A patient-specific 3D modelling and printing procedure (Figure 1), for surgical planning in case of complex heart diseases
was developed. The procedure was applied to two case studies, for which MCT scans of the chest are available. In the article, a detailed
description on the implemented patient-specific modelling procedure is provided, along with a general discussion on the potentiality
and future developments of personalized 3D modelling and printing for surgical planning and surgeons practice
Effective Geometric Restoration of Distorted Historical Document for Large-Scale Digitization
Due to storage conditions and material’s non-planar shape, geometric distortion of the 2-D content is widely present in scanned document images. Effective geometric restoration of these distorted document images considerably increases character recognition rate in large-scale digitisation. For large-scale digitisation of historical books, geometric restoration solutions expect to be accurate, generic, robust, unsupervised and reversible. However, most methods in the literature concentrate on improving restoration accuracy for specific distortion effect, but not their applicability in large-scale digitisation. This paper proposes an effective mesh based geometric restoration system, (GRLSD), for large-scale distorted historical document digitisation. In this system, an automatic mesh generation based dewarping tool is proposed to geometrically model and correct arbitrary warping historical documents. An XML based mesh recorder is proposed to record the mesh of distortion information for reversible use. A graphic user interface toolkit is designed to visually display and manually manipulate the mesh for improving geometric restoration accuracy. Experimental results show that the proposed automatic dewarping approach efficiently corrects arbitrarily warped historical documents, with an improved performance over several state-of-the-art geometric restoration methods. By using XML mesh recorder and GUI toolkit, the GRLSD system greatly aids users to flexibly monitor and correct ambiguous points of mesh for the prevention of damaging historical document images without distortions in large-scale digitalisation
Geometric correction of historical Arabic documents
Geometric deformations in historical documents significantly influence the success of both Optical Character Recognition (OCR) techniques and human readability. They may have been introduced at any time during the life cycle of a document, from when it was first printed to the time it was digitised by an imaging device. This Thesis focuses on the challenging domain of geometric correction of Arabic historical documents, where background research has highlighted that existing approaches for geometric correction of Latin-script historical documents are not sensitive to the characteristics of text in Arabic documents and therefore cannot be applied successfully. Text line segmentation and baseline detection algorithms have been investigated to propose a new more suitable one for warped Arabic historical document images. Advanced ideas for performing dewarping and geometric restoration on historical Arabic documents, as dictated by the specific characteristics of the problem have been implemented.In addition to developing an algorithm to detect accurate baselines of historical printed Arabic documents the research also contributes a new dataset consisting of historical Arabic documents with different degrees of warping severity.Overall, a new dewarping system, the first for Historical Arabic documents, has been developed taking into account both global and local features of the text image and the patterns of the smooth distortion between text lines. By using the results of the proposed line segmentation and baseline detection methods, it can cope with a variety of distortions, such as page curl, arbitrary warping and fold
Redefining A in RGBA: Towards a Standard for Graphical 3D Printing
Advances in multimaterial 3D printing have the potential to reproduce various
visual appearance attributes of an object in addition to its shape. Since many
existing 3D file formats encode color and translucency by RGBA textures mapped
to 3D shapes, RGBA information is particularly important for practical
applications. In contrast to color (encoded by RGB), which is specified by the
object's reflectance, selected viewing conditions and a standard observer,
translucency (encoded by A) is neither linked to any measurable physical nor
perceptual quantity. Thus, reproducing translucency encoded by A is open for
interpretation.
In this paper, we propose a rigorous definition for A suitable for use in
graphical 3D printing, which is independent of the 3D printing hardware and
software, and which links both optical material properties and perceptual
uniformity for human observers. By deriving our definition from the absorption
and scattering coefficients of virtual homogeneous reference materials with an
isotropic phase function, we achieve two important properties. First, a simple
adjustment of A is possible, which preserves the translucency appearance if an
object is re-scaled for printing. Second, determining the value of A for a real
(potentially non-homogeneous) material, can be achieved by minimizing a
distance function between light transport measurements of this material and
simulated measurements of the reference materials. Such measurements can be
conducted by commercial spectrophotometers used in graphic arts.
Finally, we conduct visual experiments employing the method of constant
stimuli, and derive from them an embedding of A into a nearly perceptually
uniform scale of translucency for the reference materials.Comment: 20 pages (incl. appendices), 20 figures. Version with higher quality
images: https://cloud-ext.igd.fraunhofer.de/s/pAMH67XjstaNcrF (main article)
and https://cloud-ext.igd.fraunhofer.de/s/4rR5bH3FMfNsS5q (appendix).
Supplemental material including code:
https://cloud-ext.igd.fraunhofer.de/s/9BrZaj5Uh5d0cOU/downloa
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