OCR Explained, Why You Need it

OCR stands for optical character recognition. This technology has gained significant traction due to its numerous potentials. You can use OCR when you intend to differentiate between handwritten and printed characters or numbers on digital pictures. These types of images include scanned documents and pictures that contain text.

In basic terms, OCR technology helps you read and convert handwritten and printed text into a machine-recognizable format. Therefore, OCR technology performs text recognition tasks. This text recognition process is carried out with the help of software and hardware. These technologies work together to generate machine-recognizable text from physical images and documents. In particular, many OCR technologies operate using artificial intelligence, which makes the entire text recognition process more efficient.

With the help of OCR technology, you can create a digital copy of any document. You are also able to edit the document as you require.

How OCR Works

There are several steps involved in the work of an OCR system. Below are the processes involved.

  • A physical text (printed or written) must be converted into a digital format. This can be done either with a camera or a scanner. You will want to capture all the text or pages you want to convert into machine-readable text.
  • Next, the OCR application transforms the digital document into a monochrome, which can be black and white or any other two colors.
  • The OCR software performs detailed analysis on the monochrome image. It identifies dark and light regions in the picture. The darker regions are categorized as characters, while the lighter regions fall under the background.
  • A secondary analysis is done to the darker regions. This step helps identify numeric digits and alphabets from the image.
  • Although the algorithm for each type of OCR may vary, each process is implemented one character after another. Also, each character (alphabet or number) is identified using feature recognition or pattern detection.
  • OCR through feature recognition involves using the features to identify a character from an image. Therefore, the OCR algorithm looks for curves, lines, and angles that define a character.
  • OCR through pattern detection already has a bank of characters in different sizes and fonts. So, the pattern detection algorithm tries to match the characters from the image with the stored data.

Uses of OCR

OCR has several uses in today’s world. Some of the most popular uses are highlighted below.

  • It allows for the scanning of physical files and documents into different formats. In most cases, each file format can be edited and used on different applications.
  • In addition, it eases the indexing of content made for the internet. Therefore, it makes content search engine friendly.
  • It makes data extraction, data processing, and data entry easy.
  • It helps you keep records of files, newspapers, and other essential historic documents.
  • It allows an application to directly recognize, read, and translate information from one language to another.
  • It can be used together with traffic cameras. It allows the camera to recognize and read plate numbers from vehicles and motorcycles.

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