What Is Optical Character Recognition?
What is Optical Character Recognition?
nHow Does Optical Character Recognition Work?
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nn nnOCR employs a combination of pattern recognition, artificial intelligence, and machine learning algorithms to analyse images and identify characters. The process typically involves several key steps.nImage Acquisition
nThe first step is to obtain a digital image of the text through scanning or photography. This can be images taken from a written document, letter, text, photograph, or any form of physical document that contains words.nPre-processing
nThe captured image will undergo pre-processing to enhance its quality. This may include enhancement methods such as noise reduction, image alignment, and contrast adjustments.nSegmentation
nOCR then separates the text into individual characters or words, recognising the boundaries between them.nFeature Extraction
nFeatures like shape, size, and spatial relationships are extracted from the segmented characters to create a unique profile for each.nRecognition
nThe extracted features are compared to a pre-existing database or trained model to identify the characters. Machine learning algorithms play a crucial role here, continually improving accuracy with more data.nText Extraction
nThe extracted text is then converted into a machine-encoded format that can be used by computer systems to handle further processing.nWhat Are The Different Types Of Optical Character Recognition?
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n1. Simple OCR Software
nA simple OCR system will store a variety of font and text image patterns as templates. The OCR software will then use pattern-matching algorithms to compare text images (word by word) to an internal database.nnThis solution has limitations because there are virtually unlimited font and handwriting styles, and every single type cannot be captured and stored in the database.n2. Intelligent Character Recognition Software
nModern OCR systems use intelligent character recognition (ICR) technology to read the text in the same way humans do. This method trains machines to behave in a way humans do by using machine learning software.nnA machine learning system called a neural network analyses the text over many levels, processing the image repeatedly. It looks for different image attributes, such as curves, lines, intersections, and loops, and combines the results of all these different levels of analysis to get the final result.nnEven though ICR typically processes the images one character at a time, the process is fast, with results obtained in seconds.n3. Intelligent Word Recognition
nIntelligent word recognition systems work on the same principles as ICR, but process whole word images instead of preprocessing the images into characters. Intelligent Word Recognition is the recognition of unconstrained handwritten words, recognising entire handwritten words or phrases instead of character-by-character like simple OCR technology.nnIWR technology matches handwritten or printed words to a user-defined dictionary which significantly reduces character errors encountered in typical character-based recognition engines.n4. Optical Mark Recognition
nOptical Mark Recognition (OMR) recognises the marks made on paper documents, such as forms with checks, bubbles, or boxes.nnIt allows for the quick and accurate capture of information from paper forms, making it ideal for high-volume data collection. This includes tests, surveys, elections, questionnaires, and various other forms of documents.nApplications of OCR:
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- Document Digitisation: OCR is extensively used to convert printed documents into editable and searchable digital formats. This is particularly important for industries dealing with large volumes of paperwork, such as legal, healthcare, and finance. n
- Data Extraction: Businesses can leverage OCR to extract specific information from documents, invoices, and forms. This helps to streamline data entry processes and reduces the risk of errors. n
- Text-to-Speech Technology: OCR is a fundamental component of text-to-speech applications, enabling the conversion of printed or handwritten text into audible speech. n
- Translation Services: In the realm of language translation, OCR plays a pivotal role by enabling the conversion of printed or written text into digital formats that can be easily translated. n
- Accessibility: OCR contributes significantly to making content accessible for individuals with visual impairments by converting printed or handwritten text into readable formats. n
Bottom Line
nIn essence, Optical Character Recognition (OCR) stands as a transformative technology bridging the physical and digital realms, employing advanced algorithms and machine learning to convert printed or handwritten text into machine-readable data.nnIts diverse applications, from document digitisation and data extraction to text-to-speech and translation services, underscore its pivotal role in reshaping how we interact with and leverage textual information across various industries. ultimately enhancing efficiency and accessibility in the handling of textual data.nnThe journey of OCR is far from over, with ongoing advancements ensuring that this transformative technology remains at the forefront of the digital revolution.nnnnOCR is not just limited to the mere extent of convenience — its power can also be harnessed to help in digital security processes. Within our EMAS eKYC system, OCR plays a vital role in extracting information from a person’s ID card during the ID verification process.nnUsing optical character recognition (OCR) technology, OkayID then extracts the relevant information, such as address and income details from a person’s ID document.nnInnov8tif is committed to utilising the newest technologies to help businesses streamline their onboarding processes and to bolster security against fraudulent attempts.nnTo learn more about how we implement OCR into our proof of income and address services, feel free to read our other article.nnOrnnSign up for our free newsletters herennnn
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