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In this paper a new system for dynamic signature verification is presented. It is based on the consideration that each region of an handwritten signature can convey personal characteristics in diverse domains. Therefore, a multi-expert approach is considered in which each stroke of the signature is evaluated in the most profitable domain of representation. The experimental results demonstrate the...
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 the Botanic Museum of Berlin in Germany exist about 3.5 million dried plants on paper sheets. They were collected in the last two hundred years by many collectors among those was the famous researcher “Alexander von Humboldt”. because e every collector left his handwriting on the sheet the question came up if it is possible to find out automatically which sheet belongs to Humboldt's collection...
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,...
Summary form only given. Many models have been proposed over the years to study human movements in general and handwriting in particular: models relying on neural networks, dynamics models, psychophysical models, kinematic models and models exploiting minimization principles. Among the models that can be used to provide analytical representations of a pen stroke, the Kinematic Theory of rapid human...
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...
We present a complete online handwritten character recognition system for Indian languages that handles the ambiguities in segmentation as well as recognition of the strokes. The recognition is based on a generative model of handwriting formation, coupled with a discriminative model for classification of strokes. Such an approach can seamlessly integrate language and script information in the generative...
This paper describes the efforts at MILE lab, IISc, to create a 100,000-word database each in Kannada and Tamil for the design and development of Online Handwritten Recognition. It has been collected from over 600 users in order to capture the variations in writing style. We describe features of the scripts and how the number of symbols were reduced to be able to effectively train the data for recognition...
For automatic recognition of Bangla script, only a few studies are reported in the literature, which is in contrast to the role of Bangla as one of the world's major scripts. In this paper we present a new approach to online Bangla handwriting recognition and one of the first to consider cursively written words instead of isolated characters. Our method uses a sub-stroke level feature representation...
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...
Over the last century forensic document science has developed progressively more sophisticated pattern recognition methodologies for ascertaining the authorship of disputed documents. We present a writer verification method and an evaluation of its performance on historical documents with known and unknown writers. The questioned document is compared against handwriting samples of Herman Melville,...
Text line segmentation is one of the important steps for offline handwritten text / handwriting recognition. This paper describes a novel method of text line segmentation based on the physical process of writing. The basic concept behind this segmentation method is: two successive handwritten text-line are always non-intersecting. The proof of the theory is explained with a model of pen-tip movement...
We present in this paper a new method of analysis and decomposition of handwritten documents into glyphs (graphemes) and their associated code book. The different techniques that are involved in this paper are inspired by image processing methods in a large sense and mathematical models implying graph coloring. Our approaches provide firstly a rapid and detailed characterization of handwritten shapes...
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...
A signature verification system based on video is proposed in this paper.The signature information is obtained from video of camera which is different from traditional online or offline method.First,we set the camera in upper front of the white written paper,so that we can get the signatures have the most identifiability for human recognition. We locate the pen tip position using a contour-based method...
Chinese Character Recognition generally does its best to identify a handwritten Chinese character. It seldom cares about normativity of writings. In the paper, we propose an on-line evaluation approach to normativity of Chinese character writing, which is based on position vector of strokes of character writing. The approach can find whether or not the order and location of strokes of character writing...
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...
Handwriting Analysis or Graphology is a scientific method of identifying, evaluating and understanding personality through the strokes and patterns revealed by handwriting. Handwriting reveals the true personality including emotional outlay, fears, honesty, defenses and many others. Professional handwriting examiners called graphologist often identify the writer with a piece of handwriting. Accuracy...
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