OCR is a complex technology that converts images containing text into formats with editable text. This technology is widely used in many areas. The most advanced OCR systems can handle almost any types of images, even such complex ones as scanned magazine pages with images and columns, or photos from a mobile phone. How do the modern OCR technologies work? The process of converting an image to an editable document is divided into several steps.
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A review of optical chemical structure recognition tools | Journal of Cheminformatics | Full Text
With the goal to identify and extract text strings from images in scanned documents, pictures of handwritten text, video frames, etc. Current efforts focus mostly on mainstream natural languages for which there is ample available data to be used for training, predefined language models and public dictionaries that help achieve high levels of accuracy in the OCR process. Instead, specific OCR support decreases considerably when targeting programming language s — although some works to extract source code from programming video tutorials have appeared lately [2,3,4] — and even more when addressing Domain-Specific Languages DSLs where , due to their own nature and unlike general-purpose languages GPL , we do not have predefined dictionaries or pretrained recognition algorithms available. For instance, one could parse old manuals of legacy DSLs or even conference proceedings from past or related SLE conferences to automatically extract examples, which could be later used as test data for new parsers or to train any machine learning-based algorithms. In these cases, numerous examples are needed, and common solutions such as the generation of synthetic  data may not be optimal. Additionally, DSLs are currently also documented by means of video tutorials, as in the case of general programming languages. Furthermore, there is the specific case of graphical DSLs, whose graphical notation is complemented with textual languages.
Optical Character Recognition Project Report
The project is about Optical Character Recognition. It is a process of classifying optical patterns with respect to alphanumeric or other characters. Optical character recognition process includes segmentation, feature extraction and classification.
Skip to Main Content. A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions. Optical character recognition is a science that enables to translate various types of documents or images into analyzable, editable and searchable data. The objective of this review paper is to summarize research that has been conducted on character recognition of handwritten documents and to provide research directions.