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Perturbation-based recognition is effective to recover the deformation of handwritten characters and improve the recognition performance by generating multiple distortions and selecting a distortion that best restores character deformation. Considering that the characters in a field undergo similar deformation under a consistent style, we proposed style consistent perturbation for handwritten character...
Recognition of handwritten Bangla numerals has always been an open problem for researchers. Selection of appropriate preprocessing and feature extraction techniques to achieve maximum recognition accuracy is a challenging problem. In this paper, a new Quad Tree based feature set is introduced for the recognition of handwritten Bangla numeral dataset developed here. On experimentation with the database...
In many skilled labor jobs, workers develop extremely valuable specialized knowledge about the jobs they perform. Large manufacturing companies, such as Rolls-Royce Corporation, see great value in developing software systems that can monitor skilled workers and quantify the characteristics associated with productive performance. The quantification of the characteristics associated with the most highly...
Training a computer to evaluate the aesthetics of Chinese characters provides a feedback mechanism to improve the quality of automatically generated calligraphy.
Writer recognition is a very important branch of biometrics. In our previous research, a Grid Micro-structure Feature (GMSF) based text-independent and script-independent method was adopted and high performance was obtained. However, this method is sensitive to pen-width variation in practical situation. To solve this problem, an inner and inter class variances weighted high-dimensional feature matching...
This paper introduces a pair of online and offline Chinese handwriting databases, containing samples of isolated characters and handwritten texts. The samples were produced by 1,020 writers using Anoto pen on papers for obtaining both online trajectory data and offline images. Both the online samples and offline samples are divided into six datasets, three for isolated characters (DB1.0-C1.2) and...
In this paper, we propose an overlapped handwriting input method on handheld devices, which allows users to write continuously without breaks on a single size-restricted writing area. 2 issues have been considered during the implementation of the overlapped input method: previous characters on the background may obstruct the clear viewing of current character and the messy overlapped handwriting is...
In this paper a new on-line handwriting recognition system for Arabic personal names based on Hidden Markov Model (HMM) is presented. The system is trained with the ADAB-database using two different methods: manually segmented characters and non-segmented words. This work presents a recognition system dealing with a large vocabulary of 2800 Arabic personal names using a new lexicon reduction method...
It has been 50 years since the idea popped up that calculating systems can be made on the replica of the biological neural networks. Still, the development of this science branch made the improvement of these systems possible only in the last 25-30 years. Nowadays, neural computing is a very extensive, separate science. Its solid theory basis made it possible to use them to solve many kind of problems...
This competition scenario aims at a performance comparison of several automated systems for the task of signature verification. The systems have to rate the probability of authorship and non-authorship of signatures. In particular they have to determine whether questioned signatures are simulated disguised or the normal signature of the reference writer. Furthermore, the results will be compared to...
In this paper, we present an innovative approach to integrate spatial relations in stroke clustering for handwritten Devanagari character recognition. It handles strokes of any number and order, writer independently. Learnt strokes are hierarchically agglomerated via Dynamic Time Warping based on their location and their number and stored accordingly. We experimentally validate our concept by showing...
In this paper, we propose a novel heuristic approach to segment recognizable symbols from online Kannada word data and perform recognition of the entire word. Two different estimates of first derivative are extracted from the preprocessed stroke groups and used as features for classification. Estimate 2 proved better resulting in 88% accuracy, which is 3% more than that achieved with estimate 1. Classification...
In this paper, we describe Jolly mate, a product concept that we have envisioned as assistive technology for young children with Dyslexia. Jolly mate, a digital notepad, emulates the Jolly Phonics system of teaching letter sounds and letter formation to children with dyslexia. Jolly mate in turn uses simple handwritten character recognizers created using the Lipi IDE tool from the Lipi Toolkit project,...
This paper demonstrates the effectiveness of proper and efficient features for classifying online Farsi characters. We use these features to classify the main body of Farsi letters to nine groups. We implemented our method on the main bodies of 4000 isolated letters from "TMU dataset". Correct recognition rates of 99% and 94% were achieved for training and test sets respectively.
In practical applications, errors should not be treated equally, but conditionally. In this paper, errors are categorized based on different costs in misclassification. Accordingly, the characteristics of the error categorization and the corresponding strategies for correcting them are proposed. Verification based on Arabic Handwritten Numeral Recognition is considered as one application to utilize...
Being able to search for words or phrases in historic handwritten documents is of paramount importance when preserving cultural heritage. Storing scanned pages of written text can save the information from degradation, but it does not make the textual information readily available. Automatic keyword spotting systems for handwritten historic documents can fill this gap. However, most such systems have...
The paper presents three novel features for handwritten data based identity recognition. A novel framework for combining the features for identification is presented. The framework combines the features in kernel space in MKL based framework. The application of features individually and in combination is presented for writer recognition and signature verification. The writer recognition results have...
In handwriting recognition, confusing/conflicting writing styles can result in irreducible errors, so the study of writing style consistencies is important for applications. In Arabic Handwritten Numeral Recognition, most errors occur between samples of classes two and three due to their very similar shapes in some writing styles. In this paper, an automated writing style detection process is effectively...
On-line handwriting recognition has been a frontier area of research for the last few decades under the purview of pattern recognition. Word processing turns to be a vexing experience even if it is with the assistance of an alphanumeric keyboard in Indian languages. A natural solution for this problem is offered through online character recognition. There is abundant literature on the handwriting...
We investigate the recognition of handwritten musical notation using Hidden Markov Models (HMMs). In a non-gestural approach, handwritten musical notation is entered naturally via a pen tablet as we would do using pen and paper. A sequence of observed ink patterns representing musical symbols is captured and used to construct different HMM models. The proposed approach exploits both global and local...
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