Web Science and Digital Libraries Research Group

Table 1  Soper  et al. :  Classification of common OCR error types, their descriptions, and representative examples. These categories highlight challenges in text recognition systems, such as over-segmentation of words into multiple parts, merging of separate words (under-segmentation), character misinterpretations, omissions, and the generation of spurious or nonsensical content. extracted from the 'Details' page for quick and efficient information retrieval. Optical Character Recognition  (OCR) is pivotal in various applications, including online education, industrial automation, robotics, and more. The technology is designed to extract text from different image sources, ranging from scanned documents to text embedded in complex, real-world environments. However, despite its widespread adoption, OCR continues to face significant challenges due to inaccuracies in its output, as shown in Table 1 and Table 2.  Table 2  Soper et al.: Detailed examples of OC...