نتایج جستجو برای: handwritten word recognition
تعداد نتایج: 343246 فیلتر نتایج به سال:
Behavioral studies have shown that the legibility of handwritten script hinders visual word recognition. Furthermore, when compared with printed words, lexical effects (e.g., word-frequency effect) are magnified for less intelligible (difficult) handwriting (Barnhart and Goldinger, 2010; Perea et al., 2016). This boost has been interpreted in terms greater influence top-down mechanisms during I...
Discrete Hidden Markov Model (HMM) and hybrid of Neural Network (NN) and HMM are popular methods in handwritten word recognition system. The hybrid system gives better recognition result due to better discrimination capability of the NN. A major problem in handwriting recognition is the huge variability and distortions of patterns. Elastic models based on local observations and dynamic programm...
Automatic off-line Arabic handwriting recognition still faces a big challenges. Due to the cursive nature of the Arabic language, most of published works are based on recognition of a whole word without segmentation. This paper presents a new framework for the recognition of handwritten Arabic words based on segmentation. This framework involves two phases (training phase and testing phase). In...
In this paper we present a novel approach for the recognition of offline Arabic handwritten text that is motivated by the Arabic letters’ conditional joining rules. A lexicon of Arabic words can be expressed in terms of a new alphabet of PAWs (Part of Arabic Word). PAWs can be expressed in terms of letters. The recognition problem is decomposed into two problems that are solved simultaneously. ...
Automatic recognition of historical handwritten manuscripts is a daunting task due to paper degradation over time. The performance of information retrieval algorithms depends heavily on feature detection and representation methods. Although there exist popular feature descriptors such as Scale Invariant Feature Transform and Speeded Up Robust Features, in order to represent handwritten words in...
A new method to recognise words in Arabic handwritten manuscript is presented. The method injects the spectral features extracted from an input word image to a group of previously trained word models. Each word model is a single hidden Markov model. The likelihood probability of the input pattern is calculated against each model and the pattern is assigned to the model with the highest probabil...
This paper describes a geometric approach to the difficult off-line handwritten word recognition problem. The method classifies feature trees from isolated handwritten words, measuring the distance between two trees. The nearest-neighbour method has been used to classify the prototypes and the leaving-one-out criterion has been applied in order to test the classifier.
Text line segmentation is an essential pre-processing stage for handwriting recognition in many Optical Character Recognition (OCR) systems. It is an important step because inaccurately segmented text lines will cause errors in the recognition stage. Text line segmentation of the handwritten documents is still one of the most complicated problems in developing a reliable OCR. The nature of hand...
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