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The OCR technology enables a computer system to retrieve from the invoice any type of data, such as headers, supplier information, line items, etc. The most widespread use of OCR in Finance is invoice processing. OCR Solutions for Various Industries The Finance Industryīanks as well as other finance organizations have been using character recognition apps for quite a while. Depending on its operational area, OCR technology is used in various ways. Object Character Recognition has become a primary technology in every successful business, be it in the industrial or manufacturing industry.
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Read more about how to use Object Character Recognition for Quality Control. Applying OCR solutions facilitates the process of searching and sharing also of corporate information. A key aspect of a DM application is its ability to search and edit vast document flow.
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OCR embedded mobile devices allow to scan license plates of vehicles and check against an online database whether relevant regulations are observed.ĭocument Management- Document Management (DM) refers to automated workflow of company documents. Parking validation- City governments apply mobile character recognition apps to automatically validate that cars are parked legally according to state regulations. This new feature of the character recognition apps makes smartphones more attractive for users, who no longer have to get the physical text scanned with the use of an additional device as was the case with earlier, less technologically sophisticated, systems. Mobile document scanning- an OCR-powered mobile application allows users to take a photo of a document and convert it to text data.
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Intelligent Word Recognition (IWR) is a more complex technology that, rather than working with individual characters in both printed and handwritten text, can recognize entire words, including unconstrained handwritten text and fonts. Intelligent Character Recognition (ICR) refers to a recognition engine that can analyze not only printed but also handwritten texts and process various fonts, patterns, and numbers.
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Post-processing is the process aimed at reduction of noise and errors in the converted document.Īs Document Management has become an important component of every business undergoing digitalization, it is important to differentiate clearly between such terms as Optical Character Recognition (OCR), Intelligent Character Recognition (ICR), and Intelligent Word Recognition (IWR). The classification stage allows to identify the character categories.
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The Feature Extraction is used for extracting the most relevant information from the text image, enabling the software to recognize the characters in the text. Segmentation technique is aimed at breaking a whole image into subparts, enabling the character recognition apps to easily process the document. Preprocessing incorporates thresholding (transforming of a physical document into a binary image), normalization, and noise reduction. The process refers to the training data, that are used in the OCR model. Scanning a physical document and uploading its digital copy into the OCR system. This operation includes such processes as image acquisition, preprocessing, segmentation, feature extraction, classification, and post-processing. Then it converts the text inside the image in a machine-readable text. OCR software analyzes an image for light and dark areas, identifying light areas as background and dark areas as written characters. Object Character Recognition and How it Works