Recent Trends in Pattern Recognition
S. Kannadhasan, R. Nagarajan · Advances in computational intelligence and robotics book series · 2024
Character recognition is the technique of identifying characters that have been optically processed (OCR). OCR is a method of converting a wide range of texts, PDFs, and digital pictures into an American Standard Code for Information Interchange (ASCII) or other machine-editable format in which the data may be changed or searched. Many applications, such as OCR, document categorization, data mining, and others, have demanded recent improvements in pattern recognition. Document scanners, character recognition, language recognition, security, and bank identification all rely on OCR. There are two kinds of OCR systems: online character recognition and offline character recognition. Online OCR outperforms offline OCR because characters are processed as they are written, avoiding the first step of character identification. Offline OCR is separated into two types: printed and handwritten OCR. Offline OCR is often performed by scanning typewritten or handwritten characters into a binary or grayscale picture for processing by a recognition algorithm. Scanned papers have become more valuable than typical picture files as OCR technology has advanced, converting them into text contents that computers can identify. Over the traditional process of manually retyping, OCR discovers a superior approach of automatically putting data into an electronic database. The most common issue with OCR is segmentation of linked letters or symbols. The accuracy of the OCR is proportional to the input image.