This paper presents a new hybrid approach for legal amount recognition on Italian

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 key-words: "mil", "reais/real", "

A sophisticated methodology of legal amount recognition based on the word segmentation hypotheses is introduced for automatic bank check processing. Word segmentation hypotheses are derived according to the grapheme level segmentation results of legal amount. Novel hybrid schemes of HMM

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 key-words: "mil", "reais/real", "

The system described in this paper applies Hidden Markov technology to the task of recognizing the handwritten legal amount on personal checks. We argue that the most significant source of error in handwriting recognition is the segmentation process. In traditional handwriting OCR systems

The proposed feedback-based approach as ample-mented an two steps. I n the first step, segmentataon as done accordang t o the structural features between the connected components an the legal amounts. I n the sec-ond step, a feedback process as antroduced to re-segment the parts that could

This work presents a study about feature selection and weighting for improving the recognition of handwritten words coming from Brazilian bank check lexicon. For this purpose, two global optimization methods are used: Tabu Search(TS) and Simulated Annealing(SA). These methods were combined with k-NN composing two hybrid approaches for features selection and weighting: SA/k-NN and TS/k-NN. The results show that feature sets optimized by the studied models are very efficient when compared with k-NN. Both, accuracy classification and number of features in the resultant set are considered in the conclusions. Furthermore, some new structural features extracted from image upper and lower profiles are proposed.

The system described in this paper applies Hidden Markov technology to the task of recognizing the handwritten legal amount on personal checks. We argue that the most significant source of error in handwriting recognition is the segmentation process. In traditional handwriting OCR systems

Abstract. This paper presents an efficient method of separating words in handwritten legal amounts on bank cheques based on the spatial gaps between connected components. Currently all typical existing gap measures suffer from poor performance due to the inherent problem of underestimation

This paper describes an important step towards the standardization of the research on Optical Character Recognition (OCR) in Farsi language. It describes formations of novel and standard handwritten databases including isolated digits, letters, numerical strings, Legal amounts (used for cheques