Personal identification based on handwriting
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TLDR
This paper attempts to eliminate the assumption that the written text is fixed by presenting a novel algorithm for automatic text-independent writer identification by taking a global approach based on texture analysis, where each writer's handwriting is regarded as a different texture.About:
This article is published in Pattern Recognition.The article was published on 2000-01-01 and is currently open access. It has received 341 citations till now. The article focuses on the topics: Handwriting & Intelligent character recognition.read more
Citations
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Journal ArticleDOI
A Set of Handwriting Features for Use in Automated Writer Identification
John J. H. Miller,Robert Bradley Patterson,Donald T. Gantz,Christopher P. Saunders,Mark A. Walch,JoAnn Buscaglia +5 more
TL;DR: The graph‐based system described in this article has been implemented in a highly accurate and approximately language‐independent biometric recognition system of writers of cursive documents.
Journal ArticleDOI
Quantitative characterization of morphological polymorphism of handwritten characters loops.
TL;DR: The correct classification rates reached in this study suggest that carrying out an expertise of fragmentary samples of handwriting comprising only some loops is completely possible, and differences between writers belonging to distinct groups were revealed.
Journal ArticleDOI
New mathematical and algorithmic schemes for pattern classification with application to the identification of writers of important ancient documents
Dimitris Arabadjis,Fotios Giannopoulos,Constantin Papaodysseus,Solomon Zannos,P. Rousopoulos,M. Panagopoulos,Christopher W. Blackwell +6 more
TL;DR: A novel approach is introduced for classifying curves into proper families, according to their similarity, and the methodology has been applied to the very important problem of classifying 23 Byzantine codices and 46 Ancient inscriptions to their writers, thus achieving correct dating of their content.
Journal ArticleDOI
Writer Identification using Deep Learning with FAST Keypoints and Harris corner detector
TL;DR: A writer identification system that relies on extraction of key points from handwriting and feeding small patches around these key points to a convolutional neural network for feature learning and classification is presented.
Journal ArticleDOI
Writer identification in handwritten musical scores with bags of notes
TL;DR: This work adapts the Bag of Visual Words framework to the task of writer identification in handwritten musical scores and analyzes the effect of two improvements of the representation: a Bhattacharyya embedding, which improves the results at virtually no extra cost, and a Fisher Vector representation that very significantly improves the Results at the cost of a more complex and costly representation.
References
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Journal ArticleDOI
Statistical and structural approaches to texture
TL;DR: This survey reviews the image processing literature on the various approaches and models investigators have used for texture, including statistical approaches of autocorrelation function, optical transforms, digital transforms, textural edgeness, structural element, gray tone cooccurrence, run lengths, and autoregressive models.
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Automatic signature verification and writer identification — the state of the art
Réjean Plamondon,Guy Lorette +1 more
TL;DR: A survey of the literature on automatic signature verification and writer identification by computer, and an overview of achievements in static and dynamic approaches to solving these problems, with a special focus on preprocessing techniques, feature extraction methods, comparison processes and performance evaluation.
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A review of recent texture segmentation and feature extraction techniques
Todd R. Reed,J. M. Hans du Buf +1 more
TL;DR: The area of texture segmentation has undergone tremendous growth in recent years as discussed by the authors, and there has been a great deal of activity both in the refinement of previously known approaches and in the development of completely new techniques.
Journal ArticleDOI
Text segmentation using Gabor filters for automatic document processing
TL;DR: In this paper, two-dimensional Gabor filters are used to extract texture features for each text region in a given document image, and the text in the document is considered as a textured region.
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