Section 2 gives an overview of the recent literature on deep gen- erative models, image encoders, and diagram-based tasks and datasets. Section 3 describes Paper2Fig100k, a novel dataset of research figures and texts. In Section 4 we pro- pose OCR-VQGAN, an image encoder focused in...
Paperwork- Using scanners and OCR to grep paper documents the easy way. Paperless- Scan, index, and archive all of your paper documents. gImageReader- gImageReader is a simple Gtk/Qt front-end to tesseract-ocr. VietOCR- A Java/.NET GUI frontend for Tesseract OCR engine, includingjTessBoxEdit...
This paper first summarizes the technical challenges of performing text/non-text separation. It then categorizes offline document images into different classes according to the nature of the challenges one faces, in an attempt to provide insight into various techniques presented in the literature. The...
Although such OCR-based approaches have shown promising performance, they suffer from 1) high computational costs for using OCR; 2) inflexibility of OCR models on languages or types of documents; 3) OCR error propagation to the subsequent process. To address these issues, in this paper, we ...
Before this type of OCR, teams were just processing paper to get the job done. Now, they can process paper and make the job better. How Does Handwriting OCR Work? Handwriting OCR achieves what traditional OCR never could in its ability to convert handwriting to text easily. But getting to...
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2 Literature Review This paper, to the best of the authors' knowledge, is the first work in Arabic printed text OCR investigating a novel way to extract word features in the Block-based DCT (BDCT) domain. This is based on using a Discrete one-dimensional Hidden Markov (Bakis) Model (1D...
In this paper they call a document a VRD and I’ll be sticking with it. Each document is modelled as a graph of text segments, where each text segment is comprised of the position of the segment and the text within it. The graph is comprised of nodes that represent text segments, and...
paper describesa simple andeffectivefor printed documentsin Kannada,Hindiand English text border languagerecognition technology.Thetechnology is supported by OCR system,set up toextractthe boundary ofasi ngle textinthetext image ofthe top oftheoutlineandbottom ...
In the literature, many feature types are proposed for document classification. However, an extensive and systematic evaluation of the various approaches has not yet been done. In particular, evaluations on OCR documents are very rare. In this paper we investigate seven text representations based on...