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THAI CHARACTER RECOGNITION ON TAX FORM

 

TITLE THAI CHARACTER RECOGNITION ON TAX FORM
AUTHOR PHOORAT PAKAWATHANA
DEGREE MASTER OF SCIENCE PROGRAMME IN COMPUTER SCIENCE
FACULTY FACULTY OF SCIENCE
ADVISOR SUKANYA PHONGSUPHAP
CO-ADVISOR CHOMTIP PORNPANOMCHAI
 
ABSTRACT
This research project develops a method to recognize the Thai characters on tax forms. There are five main steps in this method. 1) Preprocessing: The median filter is used to improve the quality of image by eradicating the noises and transform an image from 256 gray scale image to binary image. 2) Segmentation: The horizontal projection profile and heuristic rules are used to separate lines and then, the vertical and horizontal projection profiles are performed to segment characters. The result from this step is the single character images. 3) Feature Extraction: There are three different techniques used in this step consisting of finding the direction of the character’s contour, the density of the character and the peripheral information of character. 4) Feature Selection: Sequential Forward Floating Selection (SFFS) is performed to select the proper features generated from the previous step. 5) Recognition: The Neural Networks are used to recognize the characters in each level. In experiments, the test data having 4,000 characters, from the prepared documents obtained from a line printer and 8,391 characters from labels on tax forms are used to evaluate the system. The accuracy rates are approximately 98.88% and 93.77% respectively. The results indicate that the proposed method can work efficiently for recognition of printed Thai characters on labels on Tax form images.
KEYWORD CHARACTER RECOGNITION/ THAI CHARACTER RECOGNITION /NEURAL NETWORK/ CHARACTER SEGMENTATION/ FEATURE SELECTION/

 

 

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