Brazilian bank check handwritten legal amount recognition

This paper presents a system that is being developed for the recognition of the handwritten legal amount in Brazilian bank checks. Our strategy used to approach the handwritten legal amount recognition problem puts on evidence the keywords: "mil", "reals/real", "centavos/centavo" which are almost always present in each amount. The recognizer, based on hidden markov models, does a global word analysis, therefore, it does not carry out an explicit segmentation of words into characters or pseudo-characters. In this context, each word image is transformed into a sequence of observations using pre-processing and feature extraction stages. Our system, when tested on our database simulating Brazilian bank checks, shows the viability of our approach.

[1]  N. Otsu A threshold selection method from gray level histograms , 1979 .

[2]  Jonathan J. Hull,et al.  Large Database Organization for Document Images , 1994 .

[3]  Nikolai Gorski,et al.  The A2iA Intercheque System: Courtesy Amount and Legal Amount Recognition for French Checks , 1997, Int. J. Pattern Recognit. Artif. Intell..

[4]  Nicholas W Strathy A method for segmentation of touching handwritten numerals , 1993 .

[5]  A. Yacoubi,et al.  Modelisation markovienne de l'ecriture manuscrite application a la reconnaissance des adresses postales , 1996 .

[6]  Didier Guillevic Unconstrained handwriting recognition applied to the processing of bank cheques , 1996 .

[7]  Lambertus Schomaker A method for the determination of features used in human reading of cursive handwriting. , 1998 .

[8]  Eric Lecolinet Segmentation d'images de mots manuscrits : application a la lecture de chaines de caracteres majuscules alphanumeriques et a la lecture de l'ecriture cursive , 1990 .

[9]  Jonathan J. Hull,et al.  A Database for Handwritten Text Recognition Research , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Anil K. Jain,et al.  Feature extraction methods for character recognition-A survey , 1996, Pattern Recognit..

[11]  Venu Govindaraju,et al.  Perceptual Features for Off-line Handwritten Word Recognition: A Framework for Heuristic Prediction, Representation and Matching , 1998, SSPR/SPR.

[12]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[13]  Manuel Avila Optimisation de modèles markoviens pour la reconnaissance de l'écrit , 1996 .

[14]  Gyeonghwan Kim,et al.  Recognition of offline handwritten words and its extension to phrase recognition , 1996 .