This is the second paper in a series of two papers describing a novel approach for generalizing classical hidden Markov models using fuzzy measures and fuzzy integrals and their application to the problem of handwritten word recognition. This paper presents an application of the generalized hidden Markov models to handwritten word recognition. The system represents a word image as an ordered li...

Many off–line handwritten word recognition systems have been proposed since the early nineties. Most systems reported high recognition rates, however, they overlooked a very important factor in the process; speed factor. In this paper we explore the potential for speeding up an off–line handwritten word recognition system via concurrency. The goal of the system is to achieve both full accuracy ...

An examination of how the word recognition system is able to process handwritten words is fundamental to formulate a comprehensive model of visual word recognition. Previous research has revealed that the magnitude of lexical effects (e.g., the word-frequency effect) is greater with handwritten words than with printed words. In the present lexical decision experiments, we examined whether the q...

Slant correction is a preprocessing technique to improve segmentation and recognition accuracy for handwritten word recognition. All conventional slant correction techniques were performed by the estimation of the average slant angle and the shear transformation. In this paper, a nonuniform slant correction technique for handwritten word recognition is proposed where the slant correction proble...

Holistic Word Recognition is one of the new modalities for handwritten word identification. The holistic paradigm in handwritten word recognition treats the word as a single, indivisible entity and attempts to recognize words from their overall shape, as opposed to recognize the individual characters comprising the word. In the present work reports a longest-run based holistic feature, that has...

An active word recognition paradigm using recursive recognition processing is proposed. To achieve successful recognition result with minimum required processing e ort, recursive system architecture which has active combination of a recognition engine and a decision making module is introduced. In the proposed model, a closed loop connection between recognizer and decision maker operates recurs...

Transcription of handwritten words in historical documents is still a difficult task. When processing huge amount of pages, document centered approaches are limited by the trade-off between automatic recognition errors and the tedious aspect of human user annotation work. In this article, we investigate the use of inter page dependencies to overcome those limitations. For this, we propose a new...