22. 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, the system comprising: at least one processor; and a plurality of modules to execute on the at least one processor, the modules comprising: a character block creator to create character blocks for the characters in the text rows and to determine positions of alignments of the character blocks; and a classification system comprising: a subsets module to determine columns for the alignments of the character blocks at the positions of the alignments, each text row having a physical structure defined by the columns of the alignments of the character blocks in that text row, and to determine an initial subset of rows for each column, each initial subset of rows comprising one or more of the text rows of the at least one document image having at least one alignment of at least one character block in a selected column, each initial subset of rows having a set of columns comprising the selected column and other columns in the one or more text rows of a corresponding initial subset of rows in which the selected column is present; an optimum set module to determine an optimum set of columns for each initial subset of rows by: generating a histogram of column frequencies of the set of columns in the corresponding initial subset of rows, each column frequency comprising a number of times a particular column occurs in the corresponding initial subset of rows; determining a threshold of the column frequencies for the corresponding initial subset of rows; and selecting particular columns having the column frequency above the threshold to be included in a corresponding optimum set; a division module to: determine a final subset of rows for each initial subset of rows, each final subset of rows comprising at least one text row of the corresponding initial subset of rows having physical structures most similar to the corresponding optimum set when compared to physical structures of all text rows in the corresponding initial subset of rows; determine a confidence factor for each final subset of rows; and determine a best confidence factor for each particular text row in the at least one document image; and a classifier module to create at least one class of text rows, the at least one class comprising at least one particular text row having a same best confidence factor.
22. 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, the system comprising: at least one processor; and a plurality of modules to execute on the at least one processor, the modules comprising: a character block creator to create character blocks for the characters in the text rows and to determine positions of alignments of the character blocks; and a classification system comprising: a subsets module to determine columns for the alignments of the character blocks at the positions of the alignments, each text row having a physical structure defined by the columns of the alignments of the character blocks in that text row, and to determine an initial subset of rows for each column, each initial subset of rows comprising one or more of the text rows of the at least one document image having at least one alignment of at least one character block in a selected column, each initial subset of rows having a set of columns comprising the selected column and other columns in the one or more text rows of a corresponding initial subset of rows in which the selected column is present; an optimum set module to determine an optimum set of columns for each initial subset of rows by: generating a histogram of column frequencies of the set of columns in the corresponding initial subset of rows, each column frequency comprising a number of times a particular column occurs in the corresponding initial subset of rows; determining a threshold of the column frequencies for the corresponding initial subset of rows; and selecting particular columns having the column frequency above the threshold to be included in a corresponding optimum set; a division module to: determine a final subset of rows for each initial subset of rows, each final subset of rows comprising at least one text row of the corresponding initial subset of rows having physical structures most similar to the corresponding optimum set when compared to physical structures of all text rows in the corresponding initial subset of rows; determine a confidence factor for each final subset of rows; and determine a best confidence factor for each particular text row in the at least one document image; and a classifier module to create at least one class of text rows, the at least one class comprising at least one particular text row having a same best confidence factor. 25. The system of claim 22 wherein: each optimum set is represented by a corresponding master row having the set of columns from the corresponding initial subset of rows, each corresponding master row comprising a binary vector comprising a binary 1 in particular columns in the set of columns for the corresponding initial subset of rows that are elements of the corresponding optimum set and a binary 0 in other particular columns in the set of columns for the corresponding initial subset of rows that are not elements of the corresponding optimum set; and the division module comprises a thresholding module using a thresholding algorithm to: determine a distance threshold for each corresponding initial subset of rows for distances from each of the one or more text rows in each corresponding initial subset of rows to the corresponding master row; split the one or more text rows in each corresponding initial subset of rows into at least a first group of text rows and a second group of text rows, the first group of text rows comprising first text rows with first distances under the threshold, the second group of text rows comprising either no text rows or second text rows with second distances not under the threshold; and select the first group of text rows to be in the corresponding final subset of rows.