Abstract—Optical Character Recognition or OCR is the electronic translation of handwritten, typewritten or printed text into machine translated images. It is widely used to recognize and search text from electronic documents or to publish the text on a website. The paper presents a survey of applications of OCR in different fields and further presents the experimentation for three important applications such as Captcha, Institutional Repository and Optical Music Character Recognition. We make use of an enhanced image segmentation algorithm based on histogram equalization using genetic algorithms for optical character recognition. The paper will act as a good literature survey for researchers starting to work in the field of optical character recognition.
Index Terms—Genetic algorithm, bimodal images, Captcha, institutional repositories and digital libraries, optical music recognition, optical character recognition.
A. Singh and K. Bacchuwar are with Electrical Department of National Institute of Technology, Warangal, India (email: amarjotsingh@ieee.org).
A. Bhasin is with Electronics and Communication Department of Guru Nanak Dev University, Jalandhar, Punjab, India.
Cite: Amarjot Singh, Ketan Bacchuwar, and Akshay Bhasin, "A Survey of OCR Applications," International Journal of Machine Learning and Computing vol. 2, no. 3, pp. 314-318, 2012.