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Most ICR software has a self-learning system referred to as a neural network, which automatically updates the recognition database for new handwriting patterns.It extends the usefulness of scanning devices for the purpose of document processing, from printed character recognition (a function of OCR) to hand-written matter recognition.
Video of the process of scanning and real-time optical character recognition (OCR) with a portable scanner. Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene photo (for example the text on signs and ...
Track-while-scan (TWS) is a mode of radar operation in which the radar allocates part of its power to tracking a target or targets (up to forty with modern radar) while part of its power is allocated to scanning. [1]
gscan2pdf is an interface for scanning documents to PDF on the GNOME desktop that uses SANE to communicate with the scanner. It is available under the GPL. It includes common editing tools, e.g., for rotating or cropping pages. It is also able to perform OCR using several optional OCR tools and save a searchable PDF. PDF files can be further ...
PDF's emphasis on preserving the visual appearance of documents across different software and hardware platforms poses challenges to the conversion of PDF documents to other file formats and the targeted extraction of information, such as text, images, tables, bibliographic information, and document metadata. Numerous tools and source code ...
Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]
Theo Pavlidis' Algorithm is a well-known method for contour tracing in binary images proposed, designed to methodically detect and follow the boundaries of related components. The technique starts by locating an initial boundary pixel, which is usually the first black pixel seen while scanning the image from top to bottom and left to right.
In the second paper Tomasi and Kanade [2] used the same basic method for finding the registration due to the translation but improved the technique by tracking features that are suitable for the tracking algorithm. The proposed features would be selected if both the eigenvalues of the gradient matrix were larger than some threshold.