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Document image analysis and recognition: a survey
Компьютерная оптика, 2022 This paper analyzes the problems of document image recognition and the existing solutions. Document recognition algorithms have been studied for quite a long time, but despite this, currently, the topic is relevant and research continues, as evidenced by
V.V. Arlazarov +6 more
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Blur2Sharp: A GAN-Based Model for Document Image Deblurring
International Journal of Computational Intelligence Systems, 2021 The advances in mobile technology and portable cameras have facilitated enormously the acquisition of text images. However, the blur caused by camera shake or out-of-focus problems may affect the quality of acquired images and their use as input for ...
Hala Neji +4 more
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Document expansion for image retrieval [PDF]
, 2010 Successful information retrieval requires effective matching between the user's search request and the contents of relevant documents. Often the request entered by a user may not use the same topic relevant terms as the authors' of the documents.
Min, Jinming +3 more
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Document Skew Detection and Correction Algorithm using Wavelet and Radon Transforms [PDF]
مجلة جامعة الانبار للعلوم الصرفة, 2009 :As part of research into document image processing, an algorithm has been developed to detect and correct the degree of skew in a scanned image. The principal components of the algorithm are the wavelet and radon transforms.
F.A. Al-adhadh +2 more
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Journal of Imaging, 2018 Isolating non-text components from the text components present in handwritten document images is an important but less explored research area. Addressing this issue, in this paper, we have presented an empirical study on the applicability of various ...
Sourav Ghosh +4 more
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Multi-view and Multi-scale Fusion Attention Network for Document Image Forgery Localization [PDF]
Jisuanji kexueWith the improvement and application of various digital platforms,document images have been widely spread on the Internet.At the same time,the development of image processing technology has increased the risk of document image tampering,making it crucial
MENG Sijiang, WANG Hongxia, ZENG Qiang, ZHOU Yang
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Document Image Binarization Process
BRAIN. Broad Research in Artificial Intelligence and Neuroscience, 2023 Technology has made significant strides in recent years, which accounts for how pervasive it is in our daily lives. In order to address the fundamental issue with historical document preservation, namely their degeneration, this work suggests using new technology. The method is built on pieces of artificial intelligence that can read the writing from a
Marcel Prodan, Costin-Anton Boiangiu
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Office Documents Classification under Limited Sample. A Case of Table Detection Inside Court Files
Journal of Information and Organizational Sciences, 2022 Deep convolutional neural networks (CNNs) became an industry standard in image processing. However, in order to keep their high efficiency, a large annotated sample is required in the case of supervised learning.
Paweł Baranowski, Adrian Stepniak
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Speech and text-image processing in documents [PDF]
Proceedings of the workshop on Human Language Technology - HLT '93, 1993 Two themes have evolved in speech and text image processing work at Xerox PARC that expand and redefine the role of recognition technology in document-oriented applications. One is the development of systems that provide functionality similar to that of text processors but operate directly on audio and scanned image data. A second, related theme is the
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Bi‐level thresholding for binarisation of handwritten and printed documents
IET Computer Vision, 2015 Document image binarisation algorithms have been available in the literature for decades. However, most of the state‐of‐the‐art methods address specific image degradation or characteristics.
Ranjani J. Jennifer
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