OCR stands for Optical Character Recognition. It refers to the technology and process used to convert printed or handwritten text into digital data that can be easily edited, searched, and stored on a computer. OCR systems are designed to recognize characters or symbols in a scanned image or document and convert them into machine-readable text.
OCR technology utilizes various algorithms and machine learning techniques to analyze and interpret the visual patterns of characters, fonts, and layouts. The process typically involves several steps, including image preprocessing, segmentation, feature extraction, and character classification. Specialized software or hardware devices are often used to perform OCR tasks.
The main purpose of OCR is to automate the conversion of physical documents or images into electronic formats, thereby enabling efficient data storage, retrieval, and manipulation. OCR can be applied in a wide range of fields and industries, including document management, data entry and conversion, digital archiving, e-books, automatic number plate recognition, and more.
OCR has significantly improved productivity and streamlined processes by eliminating manual data entry and reducing human error. However, the accuracy of OCR systems can vary depending on factors such as image quality, font type, and language complexity.
In summary, OCR is a technology utilized to convert printed or handwritten text into machine-readable form, enabling the digitization and manipulation of text-based content.
