Millions of financial transactions take place every day. Associated with them are documents such as bank cheques, payment slips and bills which have to be processed. A great deal of time, effort and money will be saved if they can be entered into the computer and processed automatically. According to the specific characteristics of financial documents, it can be concluded that it is possible to build a system for recognizing specific types of financial documents, instead of a complex and general one aiming at different kinds of documents. In this paper, a financial document recognition prototype system which can process bank cheques, payment slips and bills, is presented. It consists of four major parts: (a) document image acquisition including scanning and binarization, (b) fixed document processing subsystem based on the detection of staff lines, (c) flexible document processing subsystem operating in a form description language (FDL), and (d) character recognition. Numerous experimental results are presented and discussed.>

The knowledge acquisition bottleneck has become the major impediment to the development and application of effective information systems. To remove this bottleneck, new document processing techniques must be introduced to automatically acquire knowledge from various types of documents. By presenting a survey on the techniques and problems involved, this paper aims at serving as a catalyst to stimulate research in automatic knowledge acquisition through document processing. In this study, a document is considered to have two structures: geometric structure and logical structure. These play a key role in the process of the knowledge acquisition, which can be viewed as a process of acquiring the above structures. Extracting the geometric structure from a document refers to document analysis; mapping the geometric structure into logical structure is regarded as document understanding. Both areas are described in this paper, and the basic concept of document structure and its measurement based on entropy analysis is introduced. Logical structure and geometric models are proposed. Both top-down and bottom-up approaches and their entropy analyses are presented. Different techniques are discussed with practical examples. Mapping methods, such as tree transformation, document formatting knowledge and document format description language, are described.>