{"id":72164,"date":"2023-02-20T09:51:03","date_gmt":"2023-02-20T08:51:03","guid":{"rendered":"https:\/\/www.clickworker.com\/?page_id=72164"},"modified":"2023-11-04T12:36:58","modified_gmt":"2023-11-04T11:36:58","slug":"image-transcription","status":"publish","type":"page","link":"https:\/\/www.clickworker.com\/ai-glossary\/image-transcription\/","title":{"rendered":"Image Transcription"},"content":{"rendered":"<section class=\"white section-space top_grey_separation_sm\">\r\n<div class=\"container pb-5\">\r\n<div class=\"row align-items-center justify-content-center justify-content-lg-between\">\r\n<div class=\"col-lg-6 pb-2\">\r\n\r\n<span class=\"gl_letter_offcanvas gl_single\">I<\/span>\r\n<h1 class=\"section-headline pt-4 mt-1 mb-4\"><span class=\"gl_single_headline\">Image Transcription<\/span><\/h1>\r\n<ul>\r\n \t<li><a href=\"#explanantion\">Image Transcription \u2013 Short Explanation<\/a><\/li>\r\n \t<li><a href=\"#role\">The role of AI and Deep Learning in Image Transcription<\/a><\/li>\r\n\t<li><a href=\"#ocr\">Combining Optical Character Recognition with Natural Language Processing<\/a><\/li>\r\n\t<li><a href=\"#how\">How does image transcription work?<\/a><\/li>\r\n\t<li><a href=\"#applications\">Applications of image transcription<\/a><\/li>\r\n\t<li><a href=\"#conclusion\">Conclusion<\/a><\/li>\r\n\t<li><a href=\"#faq\">FAQs<\/a><\/li>\r\n<\/ul>\r\n<\/div>\r\n\r\n\r\n\r\n<div class=\"col-auto\">\r\n\t<img decoding=\"async\" src=\"https:\/\/www.clickworker.com\/wp-content\/uploads\/2023\/03\/image-transcription.png\" alt=\"Image Transcription\" class=\"gl_image max-width-100\"><\/div>\r\n<\/div>\r\n<\/div>\r\n<\/section>\r\n\r\n<section class=\"gray section-space\">\r\n<div class=\"container\">\r\n<div class=\"row\">\r\n<div class=\"col-lg-12\">\r\n<h2 class=\"section-headline mb-4\" id=\"explanation\">What is Image Transcription?<\/h2>\r\n<p>Image transcription is the process of detecting textual information within an image and converting it to digital text. Scanned or photographed images of receipts, handwritten notes, prescriptions, or any document with some text on it cannot be edited directly with a text editor. And that is where image transcription proves to be useful. It automatically extracts the text from images and converts them to a machine-readable and editable format.<\/p>\r\n<p>With the rise of deep learning technologies in modern times, AI has proven its usefulness in image transcription. With the help of special deep learning neural networks and training dataset, AI systems can accurately detect and retrieve text within images using various technologies such as computer vision, optical character recognition (OCR), and image processing methods. And as AI becomes increasingly capable of transcribing text from images, it is finding more and more applications among businesses and industries.<\/p>\r\n\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n<\/section>\r\n<section class=\"white section-space bottom_grey_separation_sm\">\r\n<div class=\"container\">\r\n<div class=\"row\">\r\n<div class=\"col-lg-12\">\r\n<h2 class=\"section-headline mb-4\" id=\"role\">The role of AI and Deep Learning in Image Transcription<\/h2>\r\n<p>Image transcription involves two distinct tasks \u2013 text detection or recognition, and conversion. The latter part is easy. Once a system understands text within an image, it can easily create a digital file for it. The tricky part is to help computers or machines to identify and understand texts in the first place like a human would. That is why <a href=\"https:\/\/www.clickworker.com\/ai-glossary\/artificial-intelligence\/\">AI<\/a> plays an important role in image transcription systems.<\/p>\r\n<p>The ability of AI to recognize texts within images is termed as <a href=\"https:\/\/www.clickworker.com\/ai-glossary\/optical-character-recognition\/\">Optical Character Recognition (OCR)<\/a>, which is a subset of computer vision. To detect and recognize texts as accurately as humans, AI systems are trained with a special type of <a href=\"https:\/\/www.clickworker.com\/ai-glossary\/neural-networks\/\">neural network<\/a>:<\/p>\r\n<h3>Convolutional Neural Network (CNN)<\/h3>\r\n<p>A <a href=\"https:\/\/www.clickworker.com\/ai-glossary\/convolutional-neural-network\/\">CNN<\/a> is an artificial neural network designed to analyze visual data such as image recognition. One of the key features of CNN is that it can recognize patterns within images.<\/p>\r\n<p>It works by analyzing different aspects and elements of the image through multiple layers. This type of neural network is trained by providing large quantities of labeled images, which teaches it to identify different objects and patterns within those images and use the same logic to identify such elements in other newer images as well.<\/p>\r\n<p>CNN is not just used for image transcription processes but in many areas where <a href=\"https:\/\/www.clickworker.com\/ai-glossary\/computer-vision\/\">computer vision<\/a> is applied. So to make it particularly useful for OCR, such networks need to be trained specifically to identify texts in images. That means the training data should comprise of images that include texts, along with respective transcriptions of those texts.<\/p>\r\n<p>The CNN will then compare each image with its transcription and learn to detect the text based on different patterns, for example, the curve, straight lines, and angles between the lines in each letter.<br>\r\nFor greater efficiency, the training data should contain a mixture of images with both printed texts in numerous different fonts and handwritten texts in various handwritings.<\/p>\r\n\r\n<h3>Recurrent Neural Networks (RNN)<\/h3>\r\n<p><a href=\"https:\/\/www.clickworker.com\/ai-glossary\/recurrent-neural-networks\/\">RNNs<\/a> are special neural networks that are designed to work with sequential data. They are not as impactful and important for image transcription as CNNs, but they can still prove to be useful due to their features. RNNs have two distinct functions, which can simply be termed \u201cmemory\u201d and \u201cprediction.\u201d<\/p>\r\n<p>This type of neural network analyses sequential data in steps. It then stores the output of the analysis of every step into its own memory and uses it to predict the next step of the sequence.<\/p>\r\n<p>For image transcription, these features can be useful as it can help the AI system remember and predict different words, expressions, and patterns within texts. For example, if the system is processing an image of a receipt, it can predict that numerical digits will be expected after words like \u201ctotal\u201d or \u201camount.\u201d<\/p>\r\n\r\n<div align=\"center\">\r\n<p><strong>Video on Recurrent Neural Networks<\/strong><\/p>\r\n<figure>\r\n<div class=\"lyte-wrapper\" title=\"Recurrent Neural Networks (RNNs), Clearly Explained!!!\" style=\"width:420px;max-width:100%;margin:5px;\"><div class=\"lyMe\" id=\"WYL_AsNTP8Kwu80\" itemprop=\"video\" itemscope itemtype=\"https:\/\/schema.org\/VideoObject\"><div><meta itemprop=\"thumbnailUrl\" content=\"https:\/\/www.clickworker.com\/wp-content\/plugins\/wp-youtube-lyte\/lyteCache.php?origThumbUrl=https%3A%2F%2Fi.ytimg.com%2Fvi%2FAsNTP8Kwu80%2Fhqdefault.jpg\" \/><meta itemprop=\"embedURL\" content=\"https:\/\/www.youtube.com\/embed\/AsNTP8Kwu80\" \/><meta itemprop=\"duration\" content=\"PT16M37S\" \/><meta itemprop=\"uploadDate\" content=\"2022-07-11T04:00:06Z\" \/><\/div><meta itemprop=\"accessibilityFeature\" content=\"captions\" \/><div id=\"lyte_AsNTP8Kwu80\" data-src=\"https:\/\/www.clickworker.com\/wp-content\/plugins\/wp-youtube-lyte\/lyteCache.php?origThumbUrl=https%3A%2F%2Fi.ytimg.com%2Fvi%2FAsNTP8Kwu80%2Fhqdefault.jpg\" class=\"pL\"><div class=\"tC\"><div class=\"tT\" itemprop=\"name\">Recurrent Neural Networks (RNNs), Clearly Explained!!!<\/div><\/div><div class=\"play\"><\/div><div class=\"ctrl\"><div class=\"Lctrl\"><\/div><div class=\"Rctrl\"><\/div><\/div><\/div><noscript><a href=\"https:\/\/youtu.be\/AsNTP8Kwu80\" rel=\"nofollow\"><img decoding=\"async\" src=\"https:\/\/www.clickworker.com\/wp-content\/plugins\/wp-youtube-lyte\/lyteCache.php?origThumbUrl=https%3A%2F%2Fi.ytimg.com%2Fvi%2FAsNTP8Kwu80%2F0.jpg\" alt=\"Recurrent Neural Networks (RNNs), Clearly Explained!!!\" width=\"420\" height=\"216\" \/><br \/>Watch this video on YouTube<\/a><\/noscript><meta itemprop=\"description\" content=\"When you don&#039;t always have the same amount of data, like when translating different sentences from one language to another, or making stock market predictions from different companies, Recurrent Neural Networks come to the rescue. In this StatQuest, we&#039;ll show you how Recurrent Neural Networks work, one step at a time, and then we&#039;ll show you their critical flaw that will lead us to understanding Long Short-Term Memory Networks. English This video has been dubbed using an artificial voice via https:\/\/aloud.area120.google.com to increase accessibility. You can change the audio track language in the Settings menu. Spanish Este video ha sido doblado al espa\u00f1ol con voz artificial con https:\/\/aloud.area120.google.com para aumentar la accesibilidad. Puede cambiar el idioma de la pista de audio en el men\u00fa Configuraci\u00f3n. Portuguese Este v\u00eddeo foi dublado para o portugu\u00eas usando uma voz artificial via https:\/\/aloud.area120.google.com para melhorar sua acessibilidade. Voc\u00ea pode alterar o idioma do \u00e1udio no menu Configura\u00e7\u00f5es. For a complete index of all the StatQuest videos, check out... https:\/\/app.learney.me\/maps\/StatQuest ...or... https:\/\/statquest.org\/video-index\/ If you&#039;d like to support StatQuest, please consider... Patreon: https:\/\/www.patreon.com\/statquest ...or... YouTube Membership: https:\/\/www.youtube.com\/channel\/UCtYLUTtgS3k1Fg4y5tAhLbw\/join ...a cool StatQuest t-shirt or sweatshirt: https:\/\/shop.spreadshirt.com\/statquest-with-josh-starmer\/ ...buying one or two of my songs (or go large and get a whole album!) https:\/\/joshuastarmer.bandcamp.com\/ ...or just donating to StatQuest! https:\/\/www.paypal.me\/statquest Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter: https:\/\/twitter.com\/joshuastarmer 0:00 Awesome song and introduction 4:13 Basic anatomy of a recurrent neural network 5:59 Running data through a recurrent neural network 10:31 Shared weights and biases 11:23 The vanishing\/exploding gradient problem. #StatQuest #NeuralNetworks #Deeplearning #DubbedWithAloud\"><\/div><\/div><div class=\"lL\" style=\"max-width:100%;width:420px;margin:5px;\"><\/div><\/p>\r\n<figcaption><strong>Recurrent Neural Networks by StatQuest (16m:36s)<\/strong><\/figcaption>\r\n<\/figure>\r\n<\/div>\r\n\r\n\r\n<h2 class=\"section-headline mb-4\" id=\"role\">Combining Optical Character Recognition with Natural Language Processing<\/h2>\r\n<p>The efficiency of AI in image transcription can be further improved when combined with <a href=\"https:\/\/www.clickworker.com\/ai-glossary\/natural-language-processing\/\">Natural Language Processing (NLP)<\/a>. Since NLP aims to make AI systems understand language the same way as humans, it can also facilitate the output of image transcription. Because even if the OCR system makes errors in the final output, the use of NLP can correct those errors by understanding the context of the text and determining the correct word.<\/p>\r\n<p>For example, consider a receipt that contains the following text at the bottom: \u201cCaution: Goods purchased once cannot be returned.\u201d Let\u2019s say that the word \u201cCaution\u201d isn\u2019t clear in the image, and the AI system interprets it as \u201cCa t on.\u201d Here, NPL can come into play, first analyzing this error and deducing that even if corrected to \u201cCat on,\u201d it still wouldn\u2019t make sense in the given context which talks about the purchase and return of goods. It could then come to the conclusion that it must be the word \u201cCaution.\u201d<\/p>\r\n<p>Similar to this example, AI can use NLP to make contextual sense out of image-to-text transcriptions, thus further improving the efficiency of OCR systems.<\/p>\r\n\r\n<blockquote class=\"rounded\"><p class=\"pb-3\"><strong>Tip:<\/strong><\/p>\r\n<p class=\"pb-3\">Do you need support with the transcription of images? clickworker offers you the proper solution.<br\/>Learn more about our<\/p><a href=\"https:\/\/www.clickworker.com\/image-annotation-services\/\" class=\"btn btn-primary\" role=\"button\">Image Annotation Services<\/a><\/blockquote>\r\n\r\n\r\n\r\n<h2 class=\"section-headline mb-4\" id=\"how\">How Does Image Transcription Work?<\/h2>\r\n<p>In general, image transcription systems convert texts inside images into digital and editable formats in three steps:<\/p>\r\n<h3>Step 1: Image pre-processing<\/h3>\r\n<p>The pre-processing stage is where the system or software performs various changes and modifications to the image for one primary purpose: to make the text easily detectable.<br>\r\nThere are many methods and technologies for image pre-processing. What method will be applied depends on how the software has been programmed, but here are some of the general methods involved in image pre-processing:<\/p>\r\n<ul class=\"standardV8styled\">\r\n<li><strong>Image Deskewing<\/strong><br>\r\n<p>This is the process of adjusting the image\u2019s alignment. Skewed images can make it difficult for the AI to detect text lines and word sequences, so it\u2019s important to restore the alignment of images before processing.<\/p><\/li>\r\n<li><a href=\"https:\/\/vciba.springeropen.com\/articles\/10.1186\/s42492-019-0016-7\" target=\"_blank\" rel=\"noopener\">Image Denoising<\/a><br>\r\n<p>Photographs and scanned images can often contain unwanted elements such as distortions, lines, speckles, etc., which are referred to as \u201cnoise\u201d in the context of image processing. These noises disrupt the clarity of images and can obstruct the AI from detecting texts. So image denoising is done to improve the clarity of the image, especially the textual elements.<\/p><\/li>\r\n\r\n<li><strong>Image Normalization<\/strong><br>\r\n<p>If the intensity values are inconsistent throughout the image, it can make it difficult to analyze certain areas. For example, in a scanned document, the bottom part of the image may be too bright, making it difficult to detect the text in that part. In such cases, image normalization is performed to adjust the intensity values at a suitable range, allowing the OCR system to identify and read the text accurately.<\/p><\/li>\r\n\r\n\r\n<p><strong>Video on OCR system<\/strong><\/p>\r\n<div class=\"row\">\r\n<div class=\"col-12 col-lg-8 mx-auto\">\r\n<div class=\"lyte-wrapper\" title=\"Optical Character Recognition (OCR)\" style=\"width:420px;max-width:100%;margin:5px;\"><div class=\"lyMe\" id=\"WYL_or8AcS6y1xg\" itemprop=\"video\" itemscope itemtype=\"https:\/\/schema.org\/VideoObject\"><div><meta itemprop=\"thumbnailUrl\" content=\"https:\/\/www.clickworker.com\/wp-content\/plugins\/wp-youtube-lyte\/lyteCache.php?origThumbUrl=https%3A%2F%2Fi.ytimg.com%2Fvi%2For8AcS6y1xg%2Fhqdefault.jpg\" \/><meta itemprop=\"embedURL\" content=\"https:\/\/www.youtube.com\/embed\/or8AcS6y1xg\" \/><meta itemprop=\"duration\" content=\"PT6M16S\" \/><meta itemprop=\"uploadDate\" content=\"2022-08-22T11:00:33Z\" \/><\/div><meta itemprop=\"accessibilityFeature\" content=\"captions\" \/><div id=\"lyte_or8AcS6y1xg\" data-src=\"https:\/\/www.clickworker.com\/wp-content\/plugins\/wp-youtube-lyte\/lyteCache.php?origThumbUrl=https%3A%2F%2Fi.ytimg.com%2Fvi%2For8AcS6y1xg%2Fhqdefault.jpg\" class=\"pL\"><div class=\"tC\"><div class=\"tT\" itemprop=\"name\">Optical Character Recognition (OCR)<\/div><\/div><div class=\"play\"><\/div><div class=\"ctrl\"><div class=\"Lctrl\"><\/div><div class=\"Rctrl\"><\/div><\/div><\/div><noscript><a href=\"https:\/\/youtu.be\/or8AcS6y1xg\" rel=\"nofollow\"><img decoding=\"async\" src=\"https:\/\/www.clickworker.com\/wp-content\/plugins\/wp-youtube-lyte\/lyteCache.php?origThumbUrl=https%3A%2F%2Fi.ytimg.com%2Fvi%2For8AcS6y1xg%2F0.jpg\" alt=\"Optical Character Recognition (OCR)\" width=\"420\" height=\"216\" \/><br \/>Watch this video on YouTube<\/a><\/noscript><meta itemprop=\"description\" content=\"What is OCR: https:\/\/ibm.biz\/What-is-OCR Let&#039;s create automation that propels innovation: https:\/\/ibm.biz\/OCR_Automation Optical character recognition (OCR) is sometimes referred to as text recognition. An OCR program extracts and repurposes data from scanned documents, camera images and image-only pdfs. OCR software singles out letters on the image, puts them into words and then puts the words into sentences, thus enabling access to and editing of the original content. It also eliminates the need for manual data entry. Watch IBM Master Inventor, Martin Keen, explain OCR&#039;s evolution and how OCR works today. Download a free AI ebook: https:\/\/ibm.biz\/OCR_Free_AI_Ebook Get started for free on IBM Cloud: https:\/\/ibm.biz\/OCR_Free_Cloud_Account Subscribe to see more videos like this in the future \u2192 http:\/\/ibm.biz\/subscribe-now #AI #Software #ITModernization #OpticalCharacterRecognition #OCR #lightboard #IBM\"><\/div><\/div><div class=\"lL\" style=\"max-width:100%;width:420px;margin:5px;\"><\/div>\r\n<\/div>\r\n<\/div>\r\n\r\n<li><strong>Image Binarization<\/strong><br>\r\n<p>Image binarization is the process of changing color images into binary images, i.e., black and white images. It makes the process of image transcription easy because, after binarization, the bright sections are usually the background of the document, while the textual elements will be dark. So the system ignored the bright areas and focused only on the darker regions, which assists in faster and easier text recognition.<\/p><\/li>\r\n\r\n<li><strong>Image Enhancement<\/strong><br>\r\n<p>While the other methods above were specific, image enhancement is a general term that can refer to various techniques that improve the quality of an image, and in context of OCR, the quality of text within the image to be specific.<\/p>\r\n<p>In fact, some of the above-mentioned methods, like normalization and denoising, are also a type of image enhancement. But apart from those, there are quite a few other techniques, such as deblurring, gamma correction, linear contrast adjustment, and median filtering, to name a few.<br>\r\nAI-powered OCR systems may use any such techniques during the pre-processing stage if deemed necessary, and they can all be generalized as image enhancement.<\/p><\/li><\/ul>\r\n\r\n<h3>Step 2: Character\/Text Recognition<\/h3>\r\n<p>There are two primary methods for OCR systems to recognize texts and characters.<\/p>\r\n\r\n<ul class=\"standardV8styled\">\r\n<li><strong>Pattern Matching<\/strong><br>\r\n<p>In this method, the OCR system has its own library consisting of default images or patterns for every letter and various characters known as glyphs. The system then compares different elements of the image with these glyphs and looks for similar or exact matches to deduce the text\u2019s letters, words and characters.<br>\r\nThese glyphs are learned and remembered by the AI based on the training data and the variety of characters, fonts, and handwriting contained in them. The larger and more diverse the training dataset, the more efficient the system will be.<\/p>\r\n<p>In general, pattern matching is highly effective in recognizing printed texts as they are in standard font and can be matched accurately if the font and scaling is same. However, it\u2019s not as effective for handwriting recognition because handwritten texts can vary greatly in terms of font and design, and cannot be matched or compared with standard datasets, patterns, or glyphs.<\/p><\/li>\r\n\r\n<li><strong>Feature Recognition<\/strong><br>\r\n<p>In this method, the system is trained to identify texts and characters by analyzing their features rather than comparing or matching them with standard glyphs stored in its own memory or database. These \u2018features\u2019 are mostly geometrical aspects such as lines, curves, angles, intersections, etc.<\/p>\r\n<p>Again, the efficiency of AI in understanding the features of every letter and character highly relies on the diversity and size of the training data set. This method is also effective in recognizing handwritten texts since it is not limited by the condition of matching the text with a set of standard patterns.<\/p><\/li><\/ul>\r\n\r\n<h3>Step 3: Post Processing<\/h3>\r\n<p>Once the AI system or software has identified all text elements within the image, the final step involves extracting the text and finalizing it into an editable text document format. During this stage, the software may also be programmed to perform some error-checking and correction methods, such as the previously mentioned case of applying Natural Language Processing abilities.<\/p>\r\n\r\n<img decoding=\"async\" class=\"img-fluid\" src=\"https:\/\/www.clickworker.com\/wp-content\/uploads\/2023\/11\/Image-Transcription.jpg\">\r\n\r\n\r\n<h2 class=\"section-headline mb-4\" id=\"applications\">Applications of Image Transcription<\/h2>\r\n<p>Image transcription has various real-world applications that are beneficial for both general users and businesses or organizations. Here are some of the most notable applications of this technology:<\/p>\r\n\r\n<ul class=\"standardV8styled\">\r\n<li><strong>Digital documentation and record keeping<\/strong><br>\r\n<p>Many kinds of documents, such as reports, legal paperwork, contracts, daily logs, etc. are essential for businesses, so they need to keep a digital record of these documents. Manually preparing such digital records can be tedious and time-consuming. So a better solution is scanning such documents and transcribing the respective images.<\/p><\/li>\r\n\r\n<li><strong>Accounting<\/strong><br>\r\n<p>Image transcription can also be extremely useful in the accounting activities of companies. OCR systems can extract key information and data from images of receipts, bills, and invoices, such as the name of the party, amount, date, etc. All these data can be automatically recorded or further fed into dedicated accounting software. It\u2019s an effective method of automating the accounting process and keeping a record of transactional details.<\/p><\/li>\r\n\r\n<li><strong>Maintaining archives<\/strong><br>\r\n<p>Using image transcription software, various important historical documents can be scanned and converted to text documents to create digital archives. Not just documents, but even artifacts and objects containing important texts can be transcribed with OCR systems.<\/p><\/li>\r\n\r\n<li><strong>Medical records<\/strong><br>\r\n<p>The medical industry is one sector where image transcription has one of the most significant applications. A large number of medical documents are hard copies, such as forms, prescriptions, and different kinds of medical records. Maintaining digital records of such documents is a must for hospitals and medical institutions, so OCR systems can be immensely useful in the healthcare sector.<\/p><\/li><\/ul>\r\n\r\n<h2 class=\"section-headline mb-4\" id=\"conclusion\">Conclusion<\/h2>\r\n<p>Transcribing an image is the process of extracting texts from images and converting them to machine-readable formats so that they can be edited and modified with text editing software. This process of image-to-text conversion has widespread applications for businesses and organizations from various sectors.<br>\r\nWith the help of technologies like deep learning neural networks and optical character recognition (OCR), AI-powered software and systems can efficiently and accurately transcribe texts from images.<\/p>\r\n<p>So, image transcription helps to save the cost and time of maintaining digital records and documentation of important information contained within hard documents such as printed and handwritten texts, making the process much more efficient than manual transcription.<\/p>\r\n\r\n<\/div>\r\n<\/div>\r\n<\/div>\r\n<\/section>\r\n\r\n<section class=\"gray section-space\">\r\n\t\t<div class=\"mini-section-spacer\"><\/div>\r\n\t\t<div class=\"mini-section-spacer\"><\/div>\r\n\t\t<div class=\"container\">\t\t\t\r\n\t\t<h2 id=\"faq\">FAQs on Image Transcription<\/h2>\t\r\n\t\t<!--<div class=\"h2 d-block faq-snippet-heading cw-dark-gray\" data-toggle=\"collapse\" data-target=\"#faqCrowdsourcingSnippet\" role=\"button\" aria-expanded=\"false\" aria-controls=\"faqCrowdsourcingSnippet\">\r\n\t\t\t\tCrowdsourcing - Goolge FAQ Snippets\r\n\t\t\t<\/div>-->\r\n\t\t<div id=\"faqDataAnnotationSnippet\">\r\n\t\t\t\t<div class=\"row\">\r\n\t\t\t\t\t\t<div class=\"col-lg-12\">\r\n\t\t\t\t\t\t\t\t\t<section class=\"sc_fs_faq sc_card card faq-snippet collapsable\">\n\t\t\t<div>\n\t\t\t\t<h2>What is image transcription?<\/h2>\t\t\t\t<div>\n\t\t\t\t\t\t\t\t\t\t<p>\n\t\t\t\t\t\tImage transcription is the process of detecting textual information within an image and converting it to digital text. Scanned or photographed images of receipts, handwritten notes, prescriptions, or any document with some text on it cannot be edited directly with a text editor.\t\t\t\t\t<\/p>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"sc_fs_faq sc_card card faq-snippet collapsable\">\n\t\t\t<div>\n\t\t\t\t<h2>What is the role of AI in Image Transcription?<\/h2>\t\t\t\t<div>\n\t\t\t\t\t\t\t\t\t\t<p>\n\t\t\t\t\t\tImage transcription involves two distinct tasks \u2013 text detection or recognition, and conversion. The latter part is easy. Once a system understands text within an image, it can easily create a digital file for it.<br>\r\n\t\t\t\t\t\t\t\tThe tricky part is to help computers or machines to identify and understand texts in the first place like a human would. That is why AI plays an important role in image transcription systems.\t\t\t\t\t<\/p>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"sc_fs_faq sc_card card faq-snippet collapsable\">\n\t\t\t<div>\n\t\t\t\t<h2>What is the role of NLP in Image Transcription?<\/h2>\t\t\t\t<div>\n\t\t\t\t\t\t\t\t\t\t<p>\n\t\t\t\t\t\tThe efficiency of AI in image transcription can be further improved when combined with Natural Language Processing (NLP). Since NLP aims to make AI systems understand language the same way as humans, it can also facilitate the output of image transcription. Because even if the OCR system makes errors in the final output, the use of NLP can correct those errors by understanding the context of the text and determining the correct word.\t\t\t\t\t<\/p>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/section>\n\t\t\n<script type=\"application\/ld+json\">\n\t{\n\t\t\"@context\": \"https:\/\/schema.org\",\n\t\t\"@type\": \"FAQPage\",\n\t\t\"mainEntity\": [\n\t\t\t\t\t{\n\t\t\t\t\"@type\": \"Question\",\n\t\t\t\t\"name\": \"What is image transcription?\",\n\t\t\t\t\"acceptedAnswer\": {\n\t\t\t\t\t\"@type\": \"Answer\",\n\t\t\t\t\t\"text\": \"Image transcription is the process of detecting textual information within an image and converting it to digital text. Scanned or photographed images of receipts, handwritten notes, prescriptions, or any document with some text on it cannot be edited directly with a text editor.\"\n\t\t\t\t\t\t\t\t\t}\n\t\t\t}\n\t\t\t,\t\t\t\t{\n\t\t\t\t\"@type\": \"Question\",\n\t\t\t\t\"name\": \"What is the role of AI in Image Transcription?\",\n\t\t\t\t\"acceptedAnswer\": {\n\t\t\t\t\t\"@type\": \"Answer\",\n\t\t\t\t\t\"text\": \"Image transcription involves two distinct tasks \u2013 text detection or recognition, and conversion. The latter part is easy. Once a system understands text within an image, it can easily create a digital file for it.<br>\r\n\t\t\t\t\t\t\t\tThe tricky part is to help computers or machines to identify and understand texts in the first place like a human would. That is why AI plays an important role in image transcription systems.\"\n\t\t\t\t\t\t\t\t\t}\n\t\t\t}\n\t\t\t,\t\t\t\t{\n\t\t\t\t\"@type\": \"Question\",\n\t\t\t\t\"name\": \"What is the role of NLP in Image Transcription?\",\n\t\t\t\t\"acceptedAnswer\": {\n\t\t\t\t\t\"@type\": \"Answer\",\n\t\t\t\t\t\"text\": \"The efficiency of AI in image transcription can be further improved when combined with Natural Language Processing (NLP). Since NLP aims to make AI systems understand language the same way as humans, it can also facilitate the output of image transcription. Because even if the OCR system makes errors in the final output, the use of NLP can correct those errors by understanding the context of the text and determining the correct word.\"\n\t\t\t\t\t\t\t\t\t}\n\t\t\t}\n\t\t\t\t\t\t]\n\t}\n<\/script>\n\r\n\t\t\t\t\t<\/div>\r\n\t\t\t\t<\/div>\r\n\t\t\t<\/div>\r\n\t\t\t<div class=\"mini-section-spacer\"><\/div>\r\n\t\t\t<div class=\"mini-section-spacer\"><\/div>\r\n\t\t<\/div>\r\n\r\n\t<\/section>\r\n","protected":false},"excerpt":{"rendered":"<p>I Image Transcription Image Transcription \u2013 Short Explanation The role of AI and Deep Learning in Image Transcription Combining Optical Character Recognition with Natural Language Processing How does image transcription work? Applications of image transcription Conclusion FAQs What is Image Transcription? Image transcription is the process of detecting textual information within an image and converting [&hellip;]<\/p>\n","protected":false},"author":65,"featured_media":0,"parent":54483,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"blank_with_breadcrumb.php","meta":{"footnotes":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Image Transcription - AI glossary \/ term explanation<\/title>\n<meta name=\"description\" content=\"Image Transcription automatically extracts the text from images and converts them to a machine-readable and editable format.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.clickworker.com\/ai-glossary\/image-transcription\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Image Transcription - 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