However, most modern OCR applications generally use one of two methods for character identification: In simple OCR applications, the raw pixel data of each character is compared directly against a database of known alphanumeric shapes to identify the closest match. It is during the character recognition process when the OCR software converts the text found in the document into its machine language equivalent.įirst, the document is analyzed for layout, identifying the locations of text blocks and paragraphs.Then, each location is broken down further by line and then individual words.įinally, each individual character is isolated ( called “segmentation”) to be translated. This maximizes the separation between the foreground ( the text ) and the background, reducing the chance of misidentified characters. Next, the color information is discarded, and the contrast of the resulting grayscale image is increased, resulting in a high contrast black and white image ( referred to as binarization). Imperfections such as dust, stray marks, and digital artifacts are removed and edges are smoothed. In the next step, the OCR software will process the scanned image to facilitate the optimal conditions for character recognition.įirst, the software will correct any alignment issues introduced during the scanning process, rotating the image to ensure the document is properly oriented. Ideally, the scanner should be calibrated against a sample document, and in the case of bulk scanning, re-calibrated several times throughout the process. It is critical that the resulting image is an accurate representation of the original document, clear and free of any defects that could interfere with the OCR process.ĭocuments should be scanned in at the maximum resolution allowed, providing the OCR software with the best chance of accurately identifying the text. The first, and arguably most important part of the process is the initial scanning of the document. We follow a simple 4 part procedure to complete this process. OCR allows us to convert paper documents into digital files that can be searched for by any text in the file, which can be edited in a word processing software, and accessed remotely from the cloud. Optical character recognition software extracts text found in an image using a combination of computer vision, pattern recognition, and artificial intelligence.įor the sake of simplicity, we are going to looking at OCR relative to the document scanning services we provide, but the concepts are basically the same in any OCR application. OCR is an absolutely essential technology for anyone who wants to be able to digitize text-heavy documents, and make immediate use of the information they contain. The most common use of OCR technology is the extraction of printed or handwritten text from physical documents to be used and understood by computer software.īy converting image data into machine encoded text, scanned documents become significantly more functional, providing the user of the digital version with the ability to search, view, and edit it’s contents, retrieve information, and more.įor this reason, the popularity of OCR technology has grown immensely, and can frequently found in both professional and consumer grade scanning software. Optical character recognition (OCR) is technology that allows computer software to convert text found in a scanned document or image into machine-readable text.Īnyone who has ever been to the airport, sent a letter in the mail, or deposited a check at an ATM has used OCR technology.
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