[1]宋晓宁,刘梓,於东军,等.表格型票据图像手写体特殊符号的混合检测算法[J].南京理工大学学报(自然科学版),2012,36(06):0.
 SONG Xiao ning,LIU Zi,YU Dong jun,et al.Hybrid Detection Approach for Handwritten Specific Symbol in Form Bill Image[J].Journal of Nanjing University of Science and Technology,2012,36(06):0.
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表格型票据图像手写体特殊符号的混合检测算法
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
36卷
期数:
2012年06期
页码:
0
栏目:
出版日期:
2012-12-31

文章信息/Info

Title:
Hybrid Detection Approach for Handwritten Specific Symbol in Form Bill Image
作者:
宋晓宁123刘梓12於东军1杨静宇1陈天雨3
1.南京理工大学 计算机科学与工程学院,江苏 南京 210094;2.江苏尚博信息科技有限公司 博士后工作站,江苏 无锡 214072;3.江苏科技大学 计算机科学与工程学院,江苏 镇江 212003
Author(s):
SONG Xiaoning 123LIU Zi 12YU Dongjun1YANG Jingyu1CHEN Tianyu 3
1.School of Computer Science and Engineering,NUST,Nanjing 210094,China;2.Postdoctoral Research Center, Jiangsu Sunboon Information Technology Co.,Ltd.,Wuxi 214072,China;3.School of Computer Science and Engineering,Jiangsu University of Science and Technology,Zhenjiang 212003,China
关键词:
票据图像处理表格型文档手写体特殊符号目标检测稀疏表示
Keywords:
bill image processingform bill imagehandwritingspecific symbolstarget detectionsparse representation
分类号:
TP391.41
摘要:
为了解决表格型票据图像定位区域中手写体勾符号的判定问题,该文提出一种混合检测算法并应用在表格型票据图像处理中。提出基于稀疏表示的形态学链码跟踪算法从而准确标记票据的外围轮廓。提出一种最优轴投影测度算法,完成外围轮廓角点坐标检测并对其进行倾角修正。根据标准模板库中的框线特征进行模板匹配,确定特殊字符所在的定位区域,利用空间卷积算法获得勾符号的判断标准。该文算法对表格型票据图像处理具有通用性,并能有效降低大规模多种类票据内容的定位与识别难度。实际银行支票图像测试证明了算法的有效性和鲁棒性。
Abstract:
To solve the problem of recognition for handwritten tick symbols filled in form bill images,a hybrid detection approach is presented for form bill image processing.A chain code algorithm based on the sparse representation is proposed by using the morphological method to describe the external contour of form bills.An optimalaxis projection estimation algorithm is proposed for angular coordinate detection of frame lines and angle correction.By means of the frame line characteristics of standard template,the form areas of special characters are determined by template matching,and the judgment criterion of tick symbol is obtained by using the spatial convolution algorithm.This algorithm has generality for form bill image processing,and can decrease the difficulty of location and identification of largescale multiple bill images.Detection results from the practical form bill images from banks demonstrate the effectiveness of the proposed method.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2011-11-25修回日期:2012-10-19 国家自然科学基金(61100116);中国博士后科学基金(2011M500926);江苏省自然科学基金(BK2012700);江苏省博士后科学基金(1102063C);人工智能四川省重点实验室开放基金(2012RZY02) 作者简介:宋晓宁(1975-),男,副教授,博士后,主要研究方向:模式识别与智能系统,图像识别,计算机视觉等,Email:xnsong@yahoo.com.cn。
更新日期/Last Update: 2012-12-29