Knowledge-based partial matching: An efficient form classification method

Abstract

An efficient method of classifying form is proposed in this paper. Our method identifies a small number of matching areas by their distinctive images with respect to their layout structure and then form classification is performed by matching only these local regions. The process is summarized as follows. First, the form is partitioned into rectangular regions along the locations of lines of the forms. The disparity in each partitioned region of the comparing form images is measured. The penalty for each partitioned area is computed by using the pre-printed text, filled-in data, and the size of a partitioned area. The disparity and penalty are considered to compute the score to select final matching areas. By using our approach, the redundant matching areas are not processed and a feature vector of good quality can be extracted.