Extracting patron data from check images

Abstract

We describe on-going research on a system for extraction and recognition of patron data such as name and address from scanned and binarized images of US checks. Extraction of the region of interest is accomplished by a graph algorithm that operates on connected components. OCR on the region of interest involves separation of connected components into lines, and generation of multiple segmentation hypotheses and character choices for each connected component. Interpretation of the raw OCR results as addresses and names is accomplished using Checkmate, a language-based OCR interpretation engine. A description of the different system components is presented in this paper.