It’s less common knowledge exactly how many words (and keywords) Google makes of an image. It has become a common place to say that an image is worth a thousand words. And I don’t mean that in the classic “an image is worth a thousand words” metaphorical sense, but in that so much of the content and of the way content is structured has to do with the use of images as lines in an imaginary dialogue, with text embedded in those images. But let’s go back to the original question: why should we care about text that is embedded in pictures (other than logos)? The best answer is probably that… that’s just how people talk over the Internet nowadays. Obviously, there’s some interest in this. Other brand-related examples come to mind, mostly in the form of online image advertisements. This is probably why there already is patented a technology that does exactly this. Sure, it’s probably just another iteration of the brand name in many cases, but it’s a relevant reiteration of it. Logos are basically text information, in a lot of cases, but in image form. What’s the case for photo-embedded text? There are several intuitive scenarios that come to mind, out of which the case of logos seems like the most obvious. And as Google is making increasingly significant efforts in the direction of image recognition technology, having recently acquired DeepMind, it’s hard to believe that photo-embedded text is not an area of interest. In this long and (we hope) interesting article we did some interesting experiments in order to understand how Google is approaching the image search matter and to see what the implications for the SEO and digital marketing field are. At the same time, the question if text embedded in photos “can’t be read by search engines” remains. In fact, the conventional wisdom seems to be that search engines do not take into account photo-embedded text (assuming they can read it at all) and that the practice of embedding text in photos is generally a bad idea for a series of other non-SEO reasons (mostly having to do with accessibility of the information for the user). Our deep learning data extraction technology immensely reduces manual errors and saves an accountant countless hours every month.It is pretty much agreed that Google can and probably does read metadata embedded in photos, though whether that influences SEO in any way is still disputed. With Docsumo’s free OCR tool, you can accurately extract data from any image in any layout without manual setup. Normal image-viewing applications don’t allow you to extract this unstructured data from images. Most of these are manually processed which takes time and is error-prone. Identity documents, compliance documents, bank statements, invoices, and receipts are a few to name. Enterprises often receive crucial information in scanned and non-scanned image form. Some systems can reproduce formatted output that closely approximates the original document including images, columns, and other non-textual components as well. Advanced systems with intelligent OCR technology are capable of producing a high degree of recognition accuracy for most fonts, and with support for a variety of digital image file format inputs. OCR is still an evolving technology in the field of pattern recognition, artificial intelligence and computer vision. OCR technology is the way of digitizing printed texts so that they can be electronically edited, searched, stored more compactly, displayed on-line, and used in machine processes such as cognitive computing, machine translation, (extracted) text-to-speech, key data and text mining. This technology is suitable for photos of text-heavy documents and printed paper data records such as passports, invoices, bank statements, receipts, business cards, and identity verification documents. 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. OCR technology comes to rescue in this situation. It can take hours to manually pull out this data and assemble it in a structured way for record-keeping and processing. The real challenge for the operation team is to be able to extract information and data from these photos. These images can be a photo of a document, scanned document, a scene-photo, or subtitle text superimposed on an image. Organizations often receive crucial information and data in image form of documents.
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