"Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text."
The process of identifying and classifying characters within digital images of text.
Image preprocessing: Techniques used to enhance the quality of images for OCR analysis.
Segmentation: The process of separating characters or text from the rest of the image.
Feature extraction: Identifying the unique characteristics of characters or text for analysis.
Machine learning: A branch of AI that enables systems to learn and improve from experience.
Classification methods: Algorithms used to classify and categorize the extracted features into recognized characters or text.
Neural networks: A type of machine learning algorithm that simulates the human brain's learning process.
Deep learning: A subset of neural networks used for complex problems, such as OCR analysis.
Computer Vision Basics: The fundamentals of image processing, image analysis, and understanding visual data.
Pattern recognition: Techniques used for identifying patterns and similarities in the data.
Statistical algorithms: Methods used for understanding and analyzing statistical data.
Data analysis: Techniques used for analyzing large amounts of data.
Handwriting recognition: It is a type of optical character recognition that captures and interprets handwritten text.
Machine-print recognition: It is the most common type of OCR and involves recognizing printed characters by a machine.
Intelligent character recognition: It is enhanced OCR technology that can recognize both printed and cursive handwriting, and convert them into digital text.
Optical word recognition: It recognizes whole words rather than individual characters.
Optical mark recognition: It is used to recognize marks or symbols made on paper, such as checkboxes and bubbles.
Business card recognition: It involves recognizing and interpreting information from business cards, such as names, phone numbers, and addresses.
Form recognition: It is used to recognize and extract specific information from forms, such as financial documents or medical forms.
Invoice recognition: It is used to read and extract information from invoices, including vendor name, date, amount, and purchase order number.
Receipt recognition: It is similar to invoice recognition, but focuses on recognizing and extracting information from receipts.
Text recognition: It involves recognizing and capturing text from a document, such as a book or newspaper article.
Barcode and QR Code recognition: It is used to scan and interpret barcodes and QR codes.
Credit card recognition: It is used for scanning and interpreting the information on credit cards, such as the card number, expiration date, and cardholder name.
"Widely used as a form of data entry from printed paper data records – whether passport documents, invoices, bank statements, computerized receipts, business cards, mail, printed data, or any suitable documentation."
"It is a common method of digitizing printed texts so that they can be electronically edited, searched, stored more compactly, displayed online, and used in machine processes such as cognitive computing, machine translation, (extracted) text-to-speech, key data and text mining."
"OCR is a field of research in pattern recognition, artificial intelligence, and computer vision."
"Early versions needed to be trained with images of each character and worked on one font at a time."
"Advanced systems capable of producing a high degree of accuracy for most fonts are now common."
"With support for a variety of image file format inputs."
"Some systems are capable of reproducing formatted output that closely approximates the original page including images, columns, and other non-textual components."
"...so that they can be electronically edited, searched, stored more compactly, displayed online..."
"Widely used as a form of data entry from printed paper data records."
"...machine processes such as cognitive computing, machine translation, (extracted) text-to-speech, key data and text mining."
"...whether passport documents, invoices, bank statements, computerized receipts, business cards, mail, printed data, or any suitable documentation..."
"...electronically edited, searched, stored more compactly, displayed online..."
"OCR is a field of research in pattern recognition, artificial intelligence, and computer vision."
"Early versions needed to be trained with images of each character and worked on one font at a time."
"Some systems are capable of reproducing formatted output that closely approximates the original page including images, columns, and other non-textual components."
"...images of typed, handwritten or printed text into machine-encoded text."
"Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text."
"OCR is a field of research in pattern recognition, artificial intelligence, and computer vision."
"...they can be electronically edited, searched, stored more compactly, displayed online, and used in machine processes such as cognitive computing, machine translation, (extracted) text-to-speech, key data and text mining."