Offline Recognition of Large Vocabulary Cursive Handwritten Text
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Text characters embedded in images and video sequences represents a rich source of information for content-based indexing and retrieval applications. However, these text characters are difficult to be detected and recognized due to their various sizes, gra ...
In current automatic speech recognition (ASR) systems, the energy is not used as part of the feature vector in spite of being a fundamental feature in the speech signal. The noise inherent in its estimation degrades the system performance. In this report w ...
Multi-band ASR was largely inspired by the extremely high level of redundancy in the spectral signal representation which can be inferred from Fletcher's product-of-errors rule for human speech perception. Indeed, the main aim of the multi-band approach is ...
is presented. The system has no {\it a priori} knowledge of passwords. A hybrid HMM/ANN system is used to infer the phonetic transcription of the password. The emission probabilities are then modeled by a multi-Gaussians HMM model. Evaluation experiments, ...
This paper presents a cursive character recognizer, a crucial module in any Cursive Script Recognition system based on a segmentation and recognition approach. The character classification is achieved by combining the use of Neural Gas (NG) and Learning Ve ...
This paper presents a cursive character recognizer, a crucial module in any Cursive Script Recognition system based on a segmentation and recognition approach. The character classification is achieved by combining the use of Neural Gas (NG) and Learning Ve ...
Text embedded in images and videos represents a rich source of information for content-based indexing and retrieval applications. In this paper, we present a new method for localizing and recognizing text in complex images and videos. Text localization is ...
This paper presents new techniques for slant and slope removal in cursive handwritten words. Both methods require neither heuristics nor parameter tuning. This avoids the heavy experimental effort required to find the optimal configuration of a parameter s ...
A system for off-line cursive script recognition is presented. A new normalization technique (based on statistical methods) to compensate for the variability of writing style is described. The key problem of segmentation is avoided by applying a sliding wi ...
is presented. The system has no {\it a priori} knowledge of passwords. A hybrid HMM/ANN system is used to infer the phonetic transcription of the password. The emission probabilities are then modeled by a multi-Gaussians HMM model. Evaluation experiments, ...
