The question then arose as how to properly locate and align scanned characters with the assumed positions of characters generated by fonts, stored in a digital image database. This line recognition problem utilized a genetic algorithm to determine the number of lines of text in the image and their relative positions to a world coordinate system. Forty pages of text skewed at different angles test the line recognition genetic algorithm with a high degree of success.The author M. Emre Celebi implements the set of seven Hu moments listed in ( Celebi and Aslandogan, 2005) using the C programming ... Incorporation of Flusser-Suka#39;s moment code into the OCR program requires a translation of the MATLAB moment code into its equivalent C programming code. ... The next chapter describes the algorithmic implementations for the signature recognition problem.
|Title||:||Genetic Algorithms for Optical Character Recognition|
|Author||:||Joseph John Svitak (Jr)|
|Publisher||:||ProQuest - 2008|