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.
CITATION STYLE
Singh, A., Bacchuwar, K., & Bhasin, A. (2012). A Survey of OCR Applications. International Journal of Machine Learning and Computing, 314–318. https://doi.org/10.7763/ijmlc.2012.v2.137
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