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Assessing Textural Features for Writer Identification on Different Writing Styles and Forgeries
2014
2014 22nd International Conference on Pattern Recognition
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Our experimental protocol is based on the dissimilarity framework and SVM classifiers, which were trained with LBP (Local Binary Pattern) and LPQ (Local Phase Quantization). ...
Our experimental results corroborates the fact that the texture is an interesting alternative for writer identification. ...
Figure 1 . 1 Dichotomy transformation: (a) samples in the feature space (b) samples in the dissimilarity space where (+) stands for the vectors associated to the within class and (-) stands for the vectors ...
doi:10.1109/icpr.2014.55
dblp:conf/icpr/BertoliniOJS14
fatcat:w5pdjxcgdvdzpj4rfbgb5suto4
Multi Check-Sign: Integration of Multimodal Verification Using Signature Identification & Android Based Graphical Pattern Analysis
2017
International Journal for Research in Applied Science and Engineering Technology
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We proposed a new framework for verifying the handwritten signature using conjointly the CT and the feature dissimilarity measure. ...
The verification step is performed using only the feature dissimilarity measure for evaluating signature's resemblance. The goal is, We are implementing Multimodal based user verification system. ...
The verification step is performed using only the feature dissimilarity measure for evaluating signature's resemblance. ...
doi:10.22214/ijraset.2017.3025
fatcat:jnzcpaim5bcjrl7azzt6hz5gji
Improving Writer Identification Through Writer Selection
[chapter]
2015
Lecture Notes in Computer Science
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In this work we present a method for selecting instances for a writer identification system underpinned on the dissimilarity representation and a holistic representation based on texture. ...
model but also a gain in terms of identification rate. ...
In this work we deal with instance selection for writer identification using the dissimilarity representation. ...
doi:10.1007/978-3-319-25751-8_21
fatcat:cfcjkttj2zflfclnkbasonpegy
Signature Verification for Banking Sector Based on SIFT
2017
International Journal Of Engineering And Computer Science
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And finally in last phase, the SDS and SOH of the input handwriting are extracted and matched with the enrolled ones for identification. ...
This study focus on text-independent writer identification method based on scale invariant feature transform (SIFT). It consists of three phase: training, enrolment and identification phase. ...
Finally compute SOH feature vector as follows: Manhattan distance is used to measure the dissimilarity between two SDSs u and v because of its simplicity and high efficiency. ] / [ oi bin bin s Obin ...
doi:10.18535/ijecs/v6i4.68
fatcat:psttseszanh6nfaegerbyjwm54
Writer verification using texture-based features
2011
International Journal on Document Analysis and Recognition
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Textures of the handwritings are created based on the inherent properties of the writer. ...
We also address an important issue of verification system, i.e., the number of writers used for training. ...
Acknowledgments This research has been supported by The National Council for Scientific and Technological Development (CNPq) grant 306358/2008-5. ...
doi:10.1007/s10032-011-0166-4
fatcat:k26sqcm7fbfq5n6nnlpi7snjwi
Texture-based descriptors for writer identification and verification
2013
Expert systems with applications
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of references used for verification and identification, how the framework performs on the problem of writer identification, and how the dissimilarity-based approach compares to other feature-based strategies ...
Besides assessing two texture descriptors (local binary patterns and local phase quantization), we also address important issues related to the dissimilarity representation, such as the impact of the number ...
Acknowledgement This research has been supported by The National Council for Scientific and Technological Development (CNPq) Grant 301653/ 2011-9. ...
doi:10.1016/j.eswa.2012.10.016
fatcat:q3ham4nybvhqpeqmmusot4kuja
Handwriting Recognition Accuracy Improvement by Author Identification
[chapter]
2006
Lecture Notes in Computer Science
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Fig. 1 . 1 Templates of medical documents used in document type identification experiment
The dissimilarity measure d(f k , o) is in fact dissimilarity measure between original frame in the template ...
For each document type there exists its binary template image f k , k = 1,...D. The problem of document type identification can be stated as follows. ...
doi:10.1007/11785231_71
fatcat:skfzac75prgipiixq5ao5plw5m
Dissimilarity Gaussian Mixture Models for Efficient Offline Handwritten Text-Independent Identification Using SIFT and RootSIFT Descriptors
2019
IEEE Transactions on Information Forensics and Security
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While a SGMM is constructed for every writer to describe the intra-class similarity that is exhibited between the handwritten texts of the same writer, a DGMM represents the contrast or dissimilarity that ...
Handwriting biometrics is the science of identifying the behavioural aspect of an individual's writing style and exploiting it to develop automated writer identification and verification systems. ...
These populations were then used to train a binary SVM classifier where the identification was performed by generating dissimilarity vectors of the query image resulting from it's comparison against all ...
doi:10.1109/tifs.2018.2850011
fatcat:cflv2uzrfbh3pi2vkxlaqx4h6a
Prediction Of Writer Using Tamil Handwritten Document Image Based On Pooled Features
2015
Zenodo
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A new discriminative model with pooled features of handwriting is proposed and implemented using support vector machine. ...
Handwriting is a unique feature of an individual. Writer may change their handwritings according to their frame of mind and this place a risky challenge in identifying the writer. ...
ACKNOWLEDGMENT The authors are grateful to the UGC, New Delhi for having provided the fund to carry out this research work. ...
doi:10.5281/zenodo.1108868
fatcat:2ws55hhuhrbm5awlfd267ndruy
Prediction Of Writer Using Tamil Handwritten Document Image Based On Pooled Features
2015
Zenodo
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A new discriminative model with pooled features of handwriting is proposed and implemented using support vector machine. ...
Handwriting is a unique feature of an individual. Writer may change their handwritings according to their frame of mind and this place a risky challenge in identifying the writer. ...
ACKNOWLEDGMENT The authors are grateful to the UGC, New Delhi for having provided the fund to carry out this research work. ...
doi:10.5281/zenodo.1338446
fatcat:okru26lhlrdnvnbmjhkhhaqc54
Biometric and Forensic Aspects of Digital Document Processing
[chapter]
2007
Advances in Pattern Recognition
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The discussion consists of the individuality of handwriting, image pre-processing and interactive tools for forensic document examination, discriminating characteristics of handwriting, a statistical model ...
The individuality of handwriting and signatures is the basis for their relevance to authentication and forensics. This very individuality makes them also potentially useful as a biometric modality. ...
Since micro features are binary-valued several binary string distance measures can be used for similarity of characters, the most effective of which is the correlation measure [7] . ...
doi:10.1007/978-1-84628-726-8_17
fatcat:fw4br4pslnh4zhc6fapycqtl2a
Uygulamalı Bilimler ve Mühendislik
2012
Anadolu University Journal of Science and Technology. A : Applied Sciences and Engineering
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Several dissimilarity measures for binary vectors are formulated and examined for their recognition capability in handwriting identification for which the binary micro-features are used to characterize ...
Cha et al. (2005) review, categorize, and evaluate various binary vector similarity and dissimilarity measures for character recognition. ...
doaj:03041a844abf4cf785246317627dd3e9
fatcat:pwqx7sxwxrhr7icr5tmtfbblty
Handwriting Recognition with Novelty
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2105.06582v1 fatcat:v5i727f4mnhplbmgklefgvidba
This paper introduces an agent-centric approach to handle novelty in the visual recognition domain of handwriting recognition (HWR). ...
A key confound is the presence of novelty, which has continued to stymie even the best machine learning-based algorithms for these tasks. ...
However, the choice of entities, fidelity for measurement for each ontological entity and weight of significance for each entity impact the utility of dissimilarity measures (see discussion on writer similarity ...
arXiv:2105.06582v2
fatcat:xzxpl6yq4bd5zffd3fhwtcmvkq
Gradient-based approach to offline text-independent Persian writer identification
2019
IET Biometrics
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This feature vector was augmented by averaging and a codebook, which utilised augmented feature vectors, was assigned to each writer for each stroke. ...
Handwritten biometric recognition (writer identification) is a process of identifying the author of a given handwriting. This process belongs to behavioural biometric systems. ...
Writer identification or handwriting recognition can be used to determine some candidate writers based on the similarity of their handwriting to an unknown handwriting [1] . ...
doi:10.1049/iet-bmt.2018.5117
fatcat:h5acd64ut5bnvlax26ihynzqcm
Hybrid Feature Learning for Handwriting Verification
[article]
2018
arXiv
pre-print
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, AE-SIFT performs comparable to this sophisticated handwriting comparison tool. ...
We propose an effective Hybrid Deep Learning (HDL) architecture for the task of determining the probability that a questioned handwritten word has been written by a known writer. ...
If the frequency of a bin is greater than the set threshold then the value of the binary gradient feature vector for this bin is 1. ...
arXiv:1812.02621v1
fatcat:eiycyxohxzedfdb4gv4hg65fea
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