1. A method of detecting dominant points on text characters in a scanned document, comprising: executing an optical character recognition (OCR) algorithm that recognizes a text character in the scanned document; performing a table lookup that identifies one or more dominant point detection rules for detecting the dominant points; applying the one or more identified dominant point detection rules to the text character to detect dominant points on the text character; fitting one or more curves to each text character outline between neighboring dominant points to convert the text character from a bitmap to a vector representation using the detected dominant points; and storing the vectorized text character to memory for use in a vector representation of the scanned document.
1. A method of detecting dominant points on text characters in a scanned document, comprising: executing an optical character recognition (OCR) algorithm that recognizes a text character in the scanned document; performing a table lookup that identifies one or more dominant point detection rules for detecting the dominant points; applying the one or more identified dominant point detection rules to the text character to detect dominant points on the text character; fitting one or more curves to each text character outline between neighboring dominant points to convert the text character from a bitmap to a vector representation using the detected dominant points; and storing the vectorized text character to memory for use in a vector representation of the scanned document. 2. The method of claim 1 , further comprising classifying each detected dominant point as at least one of a major dominant point, a minor dominant point, and an artificial dominant point.