This makes it very easy and efficient to extract and store information from business documents, receipts, invoices, passports, etc.
#Google ocr tool manual#
OCR is increasingly being used for digitization by various industries to cut down manual workload. Microsoft has come up with an awesome mathematical application that takes as input a handwritten mathematical equation and generates the solution along with a step-by-step explanation of the working. A lot of work is going on in this field and we have made some really significant advancements. OCR is used for handwriting recognition tasks to extract information. It has been incorporated in our everyday life to an extent that we hardly ever notice it! But they surely strive to bring a better user experience. OCR has widespread applications across industries (primarily with the aim of reducing manual human effort). Popular OCR Applications in the Real World
#Google ocr tool how to#
However, with the advent of deep learning, it has become possible to get better and more generalized solutions to this problem.īefore we dive into how to build your own OCR, let’s take a look at some of the popular applications of OCR. Using these techniques together is how you can extract text from any image.īut nothing is perfect and OCR is no exception. This localization of text within the image is important for the second part of OCR, text recognition, where the text is extracted from the image. The first part is text detection where the textual part within the image is determined. These images could be of handwritten text, printed text like documents, receipts, name cards, etc., or even a natural scene photograph. OCR, or Optical Character Recognition, is a process of recognizing text inside images and converting it into an electronic form. Let’s first understand what OCR is, in case you haven’t come across this concept before. What is Optical Character Recognition (OCR)?
But advances in the computer vision and deep learning field mean we can build our own OCR system right now!īut building an OCR system isn’t a straightforward task. OCR systems used to be quite expensive and cumbersome to build a couple of decades ago. So, everything from scanning documents – bank statements, receipts, handwritten documents, coupons, etc., to reading street signs in autonomous vehicles – this all falls under the OCR umbrella. Honestly, OCR has applications in a broad range of industries and functions. We will leverage the OpenCV library and Tesseract for building the OCR systemĭo you remember the days when you had to fill in the dots of the right answer during an exam? Or how about the aptitude test you gave before your first job? I can vividly recall the olympiads and multiple-choice tests where universities and organizations used an Optical Character Recognition (OCR) system to grade the answer sheets in droves.
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