12. The system of claim 11 wherein: the clustering module determines a final distances vector for each final subset of rows, each final distances vector comprising distances of the at least one of the one or more text rows of the corresponding final subset of rows to the corresponding master row associated with the corresponding final subset of rows, each final distances vector having a final row distances average; and the clustering module determines a final matches vector for each final subset of rows, each final matches vector comprising, for each one of the at least one of the one or more text rows in the corresponding final subset of rows, a sum of matches between a binary 1 in the particular columns of the corresponding master row and another binary 1 in corresponding particular columns of the each one of the at least one of the one or more text rows, each final matches vector having a final row matches average; and the confidence factor comprises a confidence factor ratio with at least one member of a group consisting of: a normalized rows frequency multiplied by the final row matches average of the final matches vector for the corresponding final subset of rows in a numerator and the final row distances average of the final distances vector for the corresponding final subset of rows in a denominator, the normalized rows frequency comprising a first number of the at least one of the one or more text rows in the corresponding final subset of rows divided by a second number of text rows in the at least one document image; and the final row matches average of the final matches vector in the numerator and the final row distances average of the final distances vector in the denominator.
12. The system of claim 11 wherein: the clustering module determines a final distances vector for each final subset of rows, each final distances vector comprising distances of the at least one of the one or more text rows of the corresponding final subset of rows to the corresponding master row associated with the corresponding final subset of rows, each final distances vector having a final row distances average; and the clustering module determines a final matches vector for each final subset of rows, each final matches vector comprising, for each one of the at least one of the one or more text rows in the corresponding final subset of rows, a sum of matches between a binary 1 in the particular columns of the corresponding master row and another binary 1 in corresponding particular columns of the each one of the at least one of the one or more text rows, each final matches vector having a final row matches average; and the confidence factor comprises a confidence factor ratio with at least one member of a group consisting of: a normalized rows frequency multiplied by the final row matches average of the final matches vector for the corresponding final subset of rows in a numerator and the final row distances average of the final distances vector for the corresponding final subset of rows in a denominator, the normalized rows frequency comprising a first number of the at least one of the one or more text rows in the corresponding final subset of rows divided by a second number of text rows in the at least one document image; and the final row matches average of the final matches vector in the numerator and the final row distances average of the final distances vector in the denominator. 13. The system of claim 12 wherein the clustering module determines two clusters of the one or more row points for each initial subset of rows.