Document imaging/scanning approaches are essential techniques for digitalizing documents in various real-world contexts, e.g., libraries, office communication, managementof workflows, and electronic archiving [...].
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http://dx.doi.org/10.3390/s21175849 | DOI Listing |
Int J Doc Anal Recognit
January 2023
Mysuru, India Department of Sciences, Amrita School of Physical Sciences, Mysuru, Amrita Vishwa Vidyapeetham.
Automated dewarping of camera-captured handwritten documents is a challenging research problem in Computer Vision and Pattern Recognition. Most available systems assume the shape of the camera-captured image boundaries to be anywhere between trapezoidal and octahedral, with linear distortion in areas between the boundaries for dewarping. The majority of the state-of-the-art applications successfully dewarp the simple-to-medium range geometrical distortions with partial selection of control points by a user.
View Article and Find Full Text PDFSensors (Basel)
August 2022
Institute for Smart Systems Technologies, University Klagenfurt, 9020 Klagenfurt, Austria.
In this study, we propose a new model for optical character recognition (OCR) based on both CNNs (convolutional neural networks) and RNNs (recurrent neural networks). The distortions affecting the document image can take different forms, such as blur (focus blur, motion blur, etc.), shadow, bad contrast, etc.
View Article and Find Full Text PDFJ Imaging
December 2021
Visual Computing Group, Department of Electrical and Computer Engineering, Democritus University of Thrace, 67100 Xanthi, Greece.
Offline handwritten text recognition (HTR) for historical documents aims for effective transcription by addressing challenges that originate from the low quality of manuscripts under study as well as from several particularities which are related to the historical period of writing. In this paper, the challenge in HTR is related to a focused goal of the transcription of Greek historical manuscripts that contain several particularities. To this end, in this paper, a convolutional recurrent neural network architecture is proposed that comprises octave convolution and recurrent units which use effective gated mechanisms.
View Article and Find Full Text PDFSensors (Basel)
October 2021
Institute for Smart Systems Technologies, University Klagenfurt, 9020 Klagenfurt, Austria.
This paper's core objective is to develop and validate a new neurocomputing model to classify document images in particularly demanding hard conditions such as image distortions, image size variance and scale, a huge number of classes, etc. Document classification is a special machine vision task in which document images are categorized according to their likelihood. Document classification is by itself an important topic for the digital office and it has several usages.
View Article and Find Full Text PDFSensors (Basel)
August 2021
Research Center Borstel-Leibniz Lung Center, 23845 Borstel, Germany.
Document imaging/scanning approaches are essential techniques for digitalizing documents in various real-world contexts, e.g., libraries, office communication, managementof workflows, and electronic archiving [.
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