1. A method of automatically training an optical character recognition (OCR) classification engine to recognize script character segments, the method comprising: receiving a plurality of cursive script words and a ground truth corresponding to each cursive script word; performing an initial segmentation of each cursive script word into a number of character segments based on a number of characters indicated in the ground truth corresponding to each cursive script word; for each character segment in the number of character segments: comparing the ground truth of the character segment with ground truths of pre-saved character segments to find a matching ground truth; when the ground truth of the character segment matches a ground truth of one of the pre-saved character segments, then determining the character segment and the pre-saved character segment to be similar; refining a plurality of horizontal boundaries and a plurality of vertical boundaries of the character segment based on the similar pre-saved character segment to define a shape of the character segment and to eliminate a noise; and adding the character segment to the pre-saved character segments associated with the matching ground truth for subsequent recognition of an instance of the character segment.
1. A method of automatically training an optical character recognition (OCR) classification engine to recognize script character segments, the method comprising: receiving a plurality of cursive script words and a ground truth corresponding to each cursive script word; performing an initial segmentation of each cursive script word into a number of character segments based on a number of characters indicated in the ground truth corresponding to each cursive script word; for each character segment in the number of character segments: comparing the ground truth of the character segment with ground truths of pre-saved character segments to find a matching ground truth; when the ground truth of the character segment matches a ground truth of one of the pre-saved character segments, then determining the character segment and the pre-saved character segment to be similar; refining a plurality of horizontal boundaries and a plurality of vertical boundaries of the character segment based on the similar pre-saved character segment to define a shape of the character segment and to eliminate a noise; and adding the character segment to the pre-saved character segments associated with the matching ground truth for subsequent recognition of an instance of the character segment. 4. The method of claim 1 , wherein refining the initial segmentation of each cursive script word into character segments comprises determining horizontal and vertical boundaries for each character segment in order to exclude a noise.