Filters








538 Hits in 5.4 sec

Assessing Textural Features for Writer Identification on Different Writing Styles and Forgeries

Diego Bertolini, Luiz S. Oliveira, Edson Justino, Robert Sabourin
2014 2014 22nd International Conference on Pattern Recognition  
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

Kishore Kumar D
2017 International Journal for Research in Applied Science and Engineering Technology  
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]

Diego Bertolini, Luiz S. Oliveira, Robert Sabourin
2015 Lecture Notes in Computer Science  
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

Mary Jolve
2017 International Journal Of Engineering And Computer Science  
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

R. K. Hanusiak, L. S. Oliveira, E. Justino, R. Sabourin
2011 International Journal on Document Analysis and Recognition  
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

D. Bertolini, L.S. Oliveira, E. Justino, R. Sabourin
2013 Expert systems with applications  
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]

Jerzy Sas
2006 Lecture Notes in Computer Science  
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

Faraz Ahmad Khan, Fouad Khelifi, Muhammad Atif Tahir, Ahmed Bouridane
2019 IEEE Transactions on Information Forensics and Security  
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

T. Thendral, M. S. Vijaya, S. Karpagavalli
2015 Zenodo  
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

T. Thendral, M. S. Vijaya, S. Karpagavalli
2015 Zenodo  
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]

Sargur N. Srihari, Chen Huang, Harish Srinivasan, Vivek Shah
2007 Advances in Pattern Recognition  
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

Edip ŞENYÜREK, Hüseyin POLAT
2012 Anadolu University Journal of Science and Technology. A : Applied Sciences and Engineering  
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]

Derek S. Prijatelj
2021 arXiv   pre-print
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

Abdorreza Alavi Gharahbagh, Farzin Yaghmaee
2019 IET Biometrics  
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]

Mohammad Abuzar Shaikh, Mihir Chauhan, Jun Chu, Sargur Srihari
2018 arXiv   pre-print
, 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
« Previous Showing results 1 — 15 out of 538 results