This paper presents a multi-staged technique for locating the courtesy amount block on bank checks. In the case of a check processing system, many of the proposed methods are not acceptable, due to the the presence of many fonts and text sizes, as well as the short length of many text strings. This paper will describe particular methods chosen to implement a Courtesy Amount Block Locator (CABL). First, the connected components in the image are identified. Next, strings are constructed on the basis of proximity and horizontal alignment of characters. Finally a set of rules and heuristics are applied to these strings to choose the correct one. The chosen string is only reported if it passes a verification test, which includes an attempt to recognize the currency sign. Keywords: check analysis and processing, block detection, courtesy amount recognition, image processing, heuristics rules, segmentation 1 Introduction Trillions of dollars change hands each year in the form of handwritten ...

Abstract. Our research focuses on Chinese online ink matching that tries to match handwritten annotations with handwritten queries without attempting to recognize them. Previously, we proposed a semantic matching scheme that uses elastic matching with a dynamic programming approach based on the radical model of Chinese characters. By means of semantic matching, a handwritten annotation may also be retrieved independently of writers via typed text query, or stored texts can be retrieved by handwritten queries. This work concerns with the behavior of the previously proposed radical model in several aspects including character normalization, stroke segmentation, structural information, dynamic programming costs and schemes. Based on our study, a new radical model is proposed. As a result, the recall of retrieval by handwritten query reaches 90 % for the first hit (an improvement of 20 % over previous results) and the recall by text query reaches 80 % when top 20 matches are returned. 1