![]() ![]() ![]() Suppose we have a digital form that a company sends us. A computer needs to understand that each one of those forms is equivalent to the letter “A” based on the pixel orientation within a word, sentence and document. Each of us think slightly differently about how the letter “A” is formed, but all versions are acceptable. #Ocr tool parse cursive how to#Computers however, need to be instructed on how to read in the same manner. Our brains are designed to recognize characters. We recognize the words and sentences on pages regardless of the print type, such as cursive, block, print or italicized, or font. We identify the shapes of each letter and each word to form sentences as long as they are legible. Think about how our eyes differentiate the background from the actual text. Currently, OCR is used in nearly every industry including automatic cameras that read your license plate when you speed through a red light, scanning a check with your phone to deposit it in real time, or even Google Translate when you are in a foreign country and in need of a quick translation of a menu or a sign! How does OCR work? ![]() OCR’s capabilities grew exponentially with the microprocessor, resulting in additional capabilities such as price tag scanners, passport scanners and the ability to scan historically handwritten textbooks for preservation purposes. As time and technology progressed, OCR was used to digitize coupons and postal addresses. WWII and into the Cold War, OCR tools were used to convert Morse code to text. Starting in the late 1800’s through the early 1900’s, the earliest concepts of OCR were developed to help the blind read. Let us take a step back and briefly discuss what Optical Character Recognition (OCR) is so that we can understand the impact of AWS Textract. History of the Optical Character Recognition ![]()
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