43. The system of claim 34 wherein the binary average row generator is further configured to: generate one or more modified text rows using at least one process selected from another group consisting of filling gaps with projection profiling processing and extending overlapping character blocks processing, wherein the one or more modified text rows correspond to the one or more particular text rows in each of the at least two selected classes; determine a corresponding one or more binary rows for the one or more modified text rows in each of the at least two selected classes; determine a projection profile for each selected class based on the corresponding one or more binary rows; and determine the corresponding binary average row for each of the one or more classes as a function of the projection profile.
34. A system to process at least one document image comprising a plurality of text rows and a plurality of characters, each text row having at least one character, wherein the plurality of text rows have been classified into two or more classes, each class comprising one or more particular text rows, system comprising: at least one processor; a pattern matching system comprising modules executed by the at least one processor, the modules comprising: a binary average row generator to determine a corresponding binary average row for each of the one or more classes, wherein each corresponding binary average row comprises binary values specifying whether a particular column position in the corresponding binary average row comprises a character block or a white space; an average row generator to determine an average row vector for each class based on the corresponding binary average row, wherein each average row vector correspond to one particular class; an interpolation grouping module to: interpolate the average row vector for the each class to generate corresponding interpolation vector data; determine a correlation value between the corresponding interpolation vector data for at least two selected classes of text rows; a distance grouping module to: determine a distance between the corresponding binary average rows for the at least two selected classes when the correlation value is less than the threshold correlation value; compare the distance to a threshold distance; and group the at least two selected classes of text rows into the first combined class when the distance is less than the threshold distance.