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This article presents the development of an Arabic online handwriting recognition system based on neural networks approach. It offers solutions for most of the difficulties linked to Arabic script recognition. Secondly, our proposed system will be integrated in Arabic language learning tool to create educational activities and to generate adequate feedback.
This paper presents a high-performance two-stage cascade CNN model. The main idea behind the cascade CNN model is complementary classification objectives between Stage I and Stage II. Discriminative learning is introduced to train Stage II by feeding back poorly recognized training samples. Experiments have been conducted on the competitive MNIST handwritten digit database. The cascade model achieved...
We present GyroPen, a method to reconstruct the motion path for pen-like interaction from standard built-in sensors in modern smartphones. The key idea is to reconstruct a representation of the trajectory of the phone's corner that is touching a writing or drawing surface from the measurements obtained from the phone's gyroscopes and accelerometers. We propose to directly use the angular trajectory...
Identification of individuals from handwritten documents using automated recognition systems has gained significant research interest due to the wide variety of applications it offers for forensic analysis, signature verification, classification of historical writings and other document analysis tasks. In this paper, we present a framework that combines different feature space representations of handwriting...
This paper presents a novel interactive method for recognizing handwritten words, using the inertial sensor data available on smart watches. The goal is to allow the user to write with a finger, and use the smart watch sensor signals to infer what the user has written. Past work has exploited the similarity of handwriting recognition to speech recognition in order to deploy HMM based methods. In contrast...
There has been a steady increase in educational learning using information devices. In Japan, Romaji is used to input text into computers and other information devices. It was developed to describe the sound of Japanese in the Roman alphabet. Therefore, learning Romaji is important for computers literacy in Japan. We developed a support system for learning Romaji through exercises using the Kinect...
Handwriting analysis is the technique used to understand a person in a better way through his/her handwriting. By examining the handwriting, we can develop a sketch which reflects the writer's emotional outlays, fears, honesty, mental state and many other personality traits. Emotions include the interpretation, perception and response of the feelings related to the experience of any particular situation...
Hidden Markov Models (HMM) are the widely used modeling techniques for online handwriting recognition. This paper describes both stroke based and character based methods for Assamese handwritten character recognition using HMM classifier. In stroke based method, unique strokes that are used to write the characters are grouped and then HMM modeling is done for each of these selected class of strokes...
The recognition of legal amount present on a bank cheque is a big challenge because of the structural complexity of characters and variability of writing styles in automatic bank cheque processing. This paper proposes a technique of text word recognition based on template matching technique using Correlation coefficient. We have developed a database of 61 words, combination of which can represent...
Necessity of unfolding the enticing field of handwritten character recognition is revealed with the mushroom growth of portable devices. Effective human machine interaction insists the development of a reliable and efficient online handwritten character recognition system. The quest becomes more challenging when it involves Urdu script based languages especially written in Nastalique font. Urdu, in...
Online handwriting recognition has many applications and the recognition with high accuracy is essential. In this paper, we introduce a method for online handwriting Farsi character and number recognition using Hidden Markov Models (HMM). First we recognize handwriting direction then we get some statistical and formatting features. The letters are classified by means of these features and then we...
The use of information devices in educational settings has been increasing over the years. We propose a learning support system that is an expansion of the original Kinect system. The proposed expansion has been implemented using the Kinect motion capture system to recognize “air characters” written by the body actions of learners and is used in this study for practicing Japanese letters expressed...
The writer adaptation arisen with the appearance and the excessive use of Handheld devices. These devices are conceived to be used in diverse user settings which can be stationary or mobile. Most of the works tackle the writer adaptation in the "sitting at a desk" environment, nevertheless we notice a lack of contributions in the multi-environment context. In this paper we present a multi-environment...
In this article, a novel lightweight user-adaptive online handwriting recognition scheme has been presented. The present recognition approach is stroke order free. It is based on prior identification of the set of various strokes of different shapes used in writing the characters of the underlying alphabet utilizing a representative sample database. In this approach a very small number of prototypes...
This paper describes a database of on-line handwritten patterns mixed of text, figures, tables, maps, diagrams and so on. Now, pen-based and touch-based interfaces are spreading into people and their surfaces are getting large. People can write and draw mixed objects without paying attention on the difference of objects or the mode change. Moreover, they may write text in any direction in combination...
Handwritten historical documents pose extremely challenging problems for automatic analysis. This is due to the high variability observed in handwritten script, the use of writing styles and script types unknown today, the frequently lacking orthographic standardization, and the degradation of the respective documents. Therefore, it is currently out of question to develop general purpose handwriting...
This paper introduces a new offline handwriting database that was developed to be employed in performance evaluation, result comparison and development of new methods related to handwriting analysis and recognition. The database can particularly be used for signature verification, writer recognition and writer demographics classification. In addition, the database also supports isolated digit recognition,...
Handwriting is a skillful graphical shapes accomplished by human on a surface paper, wood, etc. Analyzing differences and similarities between writers in order to identify the authorship of handwritten document is called writer identification. While invariant features are the core stone to classify the writers, the importance of a specific feature has not been investigated. This study aimed to examine...
In this work, we propose a novel system for the recognition of handwritten Arabic words. It is evolved based on horizontal-vertical Hidden Markov Model and Dynamic Bayesian Network Model. Our strategy consists of looking for various HMM architectures and selecting those which provide the best recognition performance. Experiments on handwritten Arabic words from IFN/ENIT strongly support the feasibility...
Restricted Boltzmann machines (RBMs) and their variants have attracted a lot of attention recently. They have been applied widely, e.g., In handwriting recognition, document categorization and object recognition. Unfortunately, an RBM requires a large parameter space since it is a fully-connected bipartite graph, especially with high dimensional input spaces. Moreover, it is still unclear how it selects...
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