2012 International Conference on Frontiers in Handwriting Recognition最新文献_第3页

Modeling Writing Styles for Online Writer Identification: A Hierarchical Bayesian Approach 在线作者识别的写作风格建模:层次贝叶斯方法

2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.235

Arti Shivram, Chetan Ramaiah, U. Porwal, V. Govindaraju

{"title":"Modeling Writing Styles for Online Writer Identification: A Hierarchical Bayesian Approach","authors":"Arti Shivram, Chetan Ramaiah, U. Porwal, V. Govindaraju","doi":"10.1109/ICFHR.2012.235","DOIUrl":"https://doi.org/10.1109/ICFHR.2012.235","url":null,"abstract":"With the explosive growth of the tablet form factor and greater availability of pen-based direct input, writer identification in online environments is increasingly becoming critical for a variety of downstream applications such as intelligent and adaptive user environments, search, retrieval, indexing and digital forensics. Extant research has approached writer identification by using writing styles as a discriminative function between writers. In contrast, we model writing styles as a shared component of an individualâs handwriting. We develop a theoretical framework for this conceptualization and model this using a three level hierarchical Bayesian model (Latent Dirichlet Allocation). In this text-independent, unsupervised model each writerâs handwriting is modeled as a distribution over finite writing styles that are shared amongst writers. We test our model on a novel online/offline handwriting dataset IBM UB 1 which is being made available to the public. Our experiments show comparable results to current benchmarks and demonstrate the efficacy of explicitly modeling shared writing styles.","PeriodicalId":291062,"journal":{"name":"2012 International Conference on Frontiers in Handwriting Recognition","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114752624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 22

Improving Handwritten Signature-Based Identity Prediction through the Integration of Fuzzy Soft-Biometric Data 基于模糊软生物特征数据集成改进手写签名身份预测

2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.221

Márjory Da Costa-Abreu, M. Fairhurst

{"title":"Improving Handwritten Signature-Based Identity Prediction through the Integration of Fuzzy Soft-Biometric Data","authors":"Márjory Da Costa-Abreu, M. Fairhurst","doi":"10.1109/ICFHR.2012.221","DOIUrl":"https://doi.org/10.1109/ICFHR.2012.221","url":null,"abstract":"Automated identification of individuals using biometric technologies is finding increasing application in diverse areas, yet designing practical systems can still present significant challenges. Choice of the modality to adopt, the classification/matching techniques best suited to the application, the most effective sensors to use, and so on, are all important considerations, and can help to ameliorate factors which might detract from optimal performance. Less well researched, however, is how to optimise performance by means of exploiting broader-based information often available in a specific task and, in particular, the exploitation of so-called \"soft\" biometric data is often overlooked. This paper proposes a novel approach to the integration of soft biometric data into an effective processing structure for an identification task by adopting a fuzzy representation of information which is inherently continuous, using subject age as a typical example. Our results show this to be a promising methodology with possible benefits in a number of potentially difficult practical scenarios.","PeriodicalId":291062,"journal":{"name":"2012 International Conference on Frontiers in Handwriting Recognition","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123307515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Binarization of First Temple Period Inscriptions: Performance of Existing Algorithms and a New Registration Based Scheme 第一庙时期铭文的二值化:现有算法的性能和一种新的基于配准的方案

2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.187

Arie Shaus, Eli Turkel, E. Piasetzky

引用次数: 25

Learning Text-Line Segmentation Using Codebooks and Graph Partitioning 使用代码本和图分区学习文本-线分割

2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.228

Le Kang, J. Kumar, Peng Ye, D. Doermann

引用次数: 11

Online Signature Verification Based on Legendre Series Representation: Robustness Assessment of Different Feature Combinations 基于Legendre级数表示的在线签名验证:不同特征组合的鲁棒性评估

2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.251

Marianela Parodi, J. Gómez, M. Liwicki

引用次数: 15

Page Segmentation Based on Steerable Pyramid Features 基于可操纵金字塔特征的页面分割

2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.253

Mohamed Benjelil, R. Mullot, A. Alimi

引用次数: 4

Statistical Machine Translation as a Language Model for Handwriting Recognition 统计机器翻译作为手写识别的语言模型

2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.273

Jacob Devlin, M. Kamali, Krishna Subramanian, R. Prasad, P. Natarajan

引用次数: 14

Three Evaluation Criteria's towards a Comparison of Two Characters Segmentation Methods for Handwritten Arabic Script 三种评价标准对两种手写阿拉伯文字字符分割方法的比较

2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.283

F. B. Samoud, S. Maddouri, H. Amiri

引用次数: 4

Reduction of Bleed-Through Effect in Images of Chinese Bank Items 减少中国银行项目图像的渗滤效应

2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.260

Bingyu Chi, Youbin Chen

引用次数: 4

Confused Distance Maximization for Large Category Dimensionality Reduction 大类别降维的混淆距离最大化

2012 International Conference on Frontiers in Handwriting Recognition Pub Date : 2012-09-18 DOI: 10.1109/ICFHR.2012.196

Xu-Yao Zhang, Cheng-Lin Liu

{"title":"Confused Distance Maximization for Large Category Dimensionality Reduction","authors":"Xu-Yao Zhang, Cheng-Lin Liu","doi":"10.1109/ICFHR.2012.196","DOIUrl":"https://doi.org/10.1109/ICFHR.2012.196","url":null,"abstract":"The Fisher linear discriminant analysis (FDA) is the most well-known supervised dimensionality reduction model. However, when the number of classes is much larger than the reduced dimensionality, FDA suffers from the class separation problem in that it will preserve the distances of the already well-separated classes and cause a large overlap of neighboring classes. To cope with this problem, we propose a new model called confused distance maximization (CDM). The objective of CDM is to maximize the distance of the most confusable classes, according to the confusion matrix estimated from the training data with a pre-learned classifier. Compared with FDA that maximizes the sum of the distances of all class pairs, CDM is more relevant to the classification accuracy by weighting the pairwise distance according to the confusion matrix. Furthermore, CDM is computationally inexpensive which makes it indeed efficient and effective for large category problems. Experiments on two large-scale 3,755-class Chinese handwriting databases (offline and online) demonstrate that CDM can achieve the best performance compared with FDA and other competitive weighting based criteria.","PeriodicalId":291062,"journal":{"name":"2012 International Conference on Frontiers in Handwriting Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130457974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5