This course is for students who want to study on a practical, work-related one year course that has no traditional examinations.
Advanced roman OCR systems can read text in large variety of fonts, but they still have difficulty with handwritten text.
To comprehend the phenomena described in the above section, we have to look at the history of OCR [3, 4, 6], its improvement, recognition methods, computer technologies, and the differences between humans and machines [1, 2, 5, 7, 8].
An overall grade, pass, merit or distinction is then awarded.
This is equivalent to three GCSE’s at C grade, B grade, or an A grade respectively.
OCR is a playing field of research in pattern identification, artificial intelligence and machine vision.
An OCR system enables you to take a book or a magazine article, feed it directly into an electronic computer file, and then edit the file using a word processor.
It is always intriguing to be able to find ways of enabling a computer to ape human functions, like the ability to read, to write, to see things, and so on.
OCR research and development can be traced back to the early 1950s, when scientists tried to confine the images of characters and texts, first by mechanical and optical means of rotating disks and photomultiplier, flying spot scanner with a cathode ray tube lens, followed by photocells and arrays of them.
Although both recognition techniques and computers were not that powerful in the in the early hours (1960s), OCR machines tended to make masses of errors when the print quality was poor, caused either by wide disparity in type fonts and roughness of the surface of the paper or by the cotton ribbons of the typewriters .
To make OCR work proficiently and economically, there was a big ram from OCR manufacturers and suppliers toward the standardization of print fonts, paper, and ink qualities for OCR applications.