OCR, or Optical Character Recognition, is a technology used in computer science to convert different types of documents—such as scanned paper documents, PDFs, or images of text—into editable and searchable data. OCR processes an image of text and extracts the letters, numbers, and symbols into a machine-readable format. The technology involves several steps: first, the image is pre-processed to improve clarity (such as removing noise or adjusting brightness). Then, OCR algorithms analyze the image to detect the shapes of characters, often using techniques like template matching or feature-based recognition. The extracted text is then converted into editable formats such as plain text, PDFs, or Word documents. Tesseract OCR is one of the most popular open-source libraries used for this purpose. It supports over 100 languages and can be integrated with various programming languages like Python and Java. OCR technology is widely used in fields such as document digitization, receipt scanning, license plate recognition, and even in assisting visually impaired individuals by reading text aloud. While modern OCR can recognize fonts and handwriting with high accuracy, challenges remain in interpreting complex layouts, noisy images, and handwriting.
What in computer science is OCR?
Keep Reading
What does a typical API request look like for generating text using Amazon Bedrock (for instance, what parameters and payload are needed)?
A typical API request to generate text using Amazon Bedrock consists of an HTTP POST request to a model-specific endpoin
What is text classification?
Text classification is the process of categorizing text data into predefined labels or categories. This is achieved by t
How does computer vision work and what is its application?
Computer vision works by analyzing visual data (images or videos) using algorithms and AI models. It involves preprocess