Keywords : optical character recognition

Arabic Character Recognition Using Fractal Dimension

Khalil I. Alsaif; Karam Hatim Thanoon

AL-Rafidain Journal of Computer Sciences and Mathematics, 2009, Volume 6, Issue 1, Pages 169-178
DOI: 10.33899/csmj.2009.163776

In this work the concepts of the pattern recognition was used to recognize printed Arabic characters, and the Fractal geometric dimension method was used.
The input for the system is image, with bitmap format , then the image of character is recognized, and after that it is feeding to the OCR system. A feature space containing the values of the fractal dimension for the letters of Arabic was constructed. These features were used in the recognition phase. In this phase a comparison was made between the values in the feature space and the values of the letter inputs to be recognized, the comparison was done by the minimum Euclidian distance. Results of this work are 75% succeeded. And Matlab 6.5 is used to write the functions and subroutines for this work.

Recognition English Letters Using Invariant Moment in Extracting Properties of Images

Hadia Saleh Abdullah

AL-Rafidain Journal of Computer Sciences and Mathematics, 2005, Volume 2, Issue 1, Pages 69-82
DOI: 10.33899/csmj.2005.164074

In this research, a study of printed English characters properties for Optical Character Recognition is done using the invariant moment method to evaluate the character properties due to it’s resistance against the rotation, scaling and shifting work. In this, also preprocessing the text and recognized it.The image text is segment often  two dissuasion methods are used to measure the distance between the moments of the new characters and the stored moments, this method is the Euclidean distance which gives high recognition factor.Due to the property of independence of the English characters, the evaluation of the seven moment of the printed character is so easy, so we evaluate the moments of English character in a different position and different size for each character by rotating the character from 45° to 360°. As a result, the invariant moment method has high ability for the recognition use, if its adopted in English Optical Character Recognition the recognition rate equals 85%.