Discriminative quadratic feature learning for handwritten Chinese character recognition
Zhou, Ming-Ke; Zhang, Xu-Yao; Yin, Fei; Liu, Cheng-Lin
2016
发表期刊PATTERN RECOGNITION
卷号49期号:1页码:7-18
文章类型Article
摘要In this paper, we propose a feature learning method for handwritten Chinese character recognition (HCCR), called discriminative quadratic feature learning (DQFL). Based on original gradient direction feature representation, quadratic correlation between features is used to promote the feature dimensionality, then discriminative feature extraction (DFE) is used for dimensionality reduction. By combining dimensionality promotion and reduction, we can learn a much more discriminative and nonlinear feature representation, which can then boost the classification accuracy significantly. For dimensionality promotion, two types of correlation are exploited, namely, statistical correlation and spatial correlation. Statistical correlation is computed on multiple local feature vectors in different regions of the character image; while spatial correlation encodes the dependency between features of two positions. Feature correlation increases the dimensionality by over 40,000. DFE then reduces the dimensionality to less than 300 without losing discriminability. Classification is performed using nearest prototype classifier (NPC), modified quadratic discriminant function (MQDF) and discriminative learning quadratic discriminant function (DLQDF). In experiments on the CASIA-HWDB1.1 standard dataset, the proposed DQFL method improves the test accuracies of NPC, MQDF and DLQDF by 4.94%, 1.83%, and 1.82%, respectively. The test accuracy is further improved by training set expansion. On the ICDAR 2013 Chinese handwriting recognition competition dataset, the proposed DQFLA+DLQDF classifier outperforms the best participating system based on deep convolutional neural network (CNN), while the test speed is much faster. (C) 2015 Elsevier Ltd. All rights reserved.
关键词Handwritten Chinese Character Recognition Discriminative Feature Learning Quadratic Correlation Dimensionality Promotion Training Set Expansion
WOS标题词Science & Technology ; Technology
DOI10.1016/j.patcog.2015.07.007
关键词[WOS]FEATURE-EXTRACTION ; NUMERAL RECOGNITION ; BENCHMARKING ; DATABASES ; ONLINE ; LINE
收录类别SCI
语种英语
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号WOS:000363077400001
引用统计
被引频次:8[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/10335
专题模式识别国家重点实验室_模式分析与学习
通讯作者Liu, Cheng-Lin
作者单位Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Zhou, Ming-Ke,Zhang, Xu-Yao,Yin, Fei,et al. Discriminative quadratic feature learning for handwritten Chinese character recognition[J]. PATTERN RECOGNITION,2016,49(1):7-18.
APA Zhou, Ming-Ke,Zhang, Xu-Yao,Yin, Fei,&Liu, Cheng-Lin.(2016).Discriminative quadratic feature learning for handwritten Chinese character recognition.PATTERN RECOGNITION,49(1),7-18.
MLA Zhou, Ming-Ke,et al."Discriminative quadratic feature learning for handwritten Chinese character recognition".PATTERN RECOGNITION 49.1(2016):7-18.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
MKZhou2016-PR.pdf(1397KB)期刊论文作者接受稿开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Zhou, Ming-Ke]的文章
[Zhang, Xu-Yao]的文章
[Yin, Fei]的文章
百度学术
百度学术中相似的文章
[Zhou, Ming-Ke]的文章
[Zhang, Xu-Yao]的文章
[Yin, Fei]的文章
必应学术
必应学术中相似的文章
[Zhou, Ming-Ke]的文章
[Zhang, Xu-Yao]的文章
[Yin, Fei]的文章
相关权益政策
暂无数据
收藏/分享
文件名: MKZhou2016-PR.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。