نتایج جستجو برای: persian handwritten letters recognition

تعداد نتایج: 287019  

2014
Keivan Borna Vahid Haji Hashemi

This paper aims to improve the feature extraction of Persian handwritten number recognition systems. In this paper, we introduced nine new features for detection and recognition of Persian handwritten digits using the technique of finding the smallest enclosing disc in computational geometry. All these features are based on the geometry form of numbers and are much better than the features in t...

2003
Javad Sadri Ching Y. Suen Tien D. Bui

A new method for recognition of isolated handwritten Arabic/Persian digits is presented. This method is based on Support Vector Machines (SVMs), and a new approach of feature extraction. Each digit is considered from four different views, and from each view 16 features are extracted and combined to obtain 64 features. Using these features, multiple SVM classifiers are trained to separate differ...

2008
Sara Izadi Mehdi Haji Ching Y. Suen

The cursive nature of Persian alphabet, and the complex and convoluted rules regarding this script cause major challenges to segmentation as well as recognition of Persian words. We propose a new segmentation algorithm for the main stroke of online Persian handwritten words. Using this segmentation, we present a perturbation method which is used to generate artificial samples from handwritten w...

This paper presents the results of Persian handwritten word recognition based on Mixture of Experts technique. In the basic form of ME the problem space is automatically divided into several subspaces for the experts, and the outputs of experts are combined by a gating network. In our proposed model, we used Mixture of Experts Multi Layered Perceptrons with Momentum term, in the classification ...

Journal: :Human brain mapping 2011
Marieke Longcamp Yevhen Hlushchuk Riitta Hari

In models of letter recognition, handwritten letters are considered as a particular font exemplar, not qualitatively different in their processing from printed letters. Yet, some data suggest that recognizing handwritten letters might rely on distinct processes, possibly related to motor knowledge. We applied functional magnetic resonance imaging to compare the neural correlates of perceiving h...

The Joint-up, cursive form of Persian words and immense variety of its scripts, also different figures of Persian letters depending on their sitting positions in the words, have turned the Persian handwritings recognition to an intense challenge. The major obstacle of the most often recognition ways, is their inattention to sentence contexture which causes utilizing of a word with correct appea...

1995
Homayoon S.M. Beigi Krishna Nathan Jayashree Subrahmonia

This paper discusses a probabilistic on-line handwriting recognition scheme, based on Hidden Markov Models (HMM's), and its implementation for recognizing handwritten words captured from a tablet. Statistical methods, such as HMM's have been used successfully for speech recognition. These methods have recently been applied to the problem of handwriting recognition as well. This paper, discusses...

Journal: :JDCTA 2009
Reza Ebrahimpour Mohammad R. Moradian Alireza Esmkhani Farzad M. Jafarlou

A method for recognition of Persian handwritten digits based on characterization loci and mixture of experts is proposed. This method utilizes the characterization loci, as the main feature. In the classification stage of our proposed method the mixture of experts are applied. This recognition method is applied to Farsi hand-written digits in the HODA database. The experimental results support ...

2011
Laslo Dinges Ayoub Al-Hamadi Moftah Elzobi Zaher Al Aghbari Hassan Mustafa

The world heritage of handwritten Arabic documents is huge however only manual indexing and retrieval techniques of the content of these documents are available. To facilitate an automatic retrieval of such handwritten Arabic document, a number of automatic recognition systems for handwritten Arabic words have been proposed. Nevertheless, these systems suffer from low recognition accuracy due t...

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