Combined Document/Business Card Detector for Proactive Document-Based Services on the Smartphone

被引:0
作者
Kim, Yong-Joong [1 ]
Kim, Yonghyun [1 ]
Kang, Bong-Nam [2 ]
Kim, Daijin [1 ,2 ]
机构
[1] Pohang Univ Sci & Technol, Dept Comp Sci & Engn, 77 Cheongam Ro, Pohang 37673, Gyeongbuk, South Korea
[2] Pohang Univ Sci & Technol, Dept Creat IT Engn, Pohang 37673, Gyeongbuk, South Korea
来源
NEURAL INFORMATION PROCESSING, ICONIP 2015, PT IV | 2015年 / 9492卷
关键词
Block-based image segmentation; Document/business card classification; Document detector; Business card detector; IMAGE CLASSIFICATION; LINES;
D O I
10.1007/978-3-319-26561-2_47
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we present a novel combined detector of document and business card. To detect document or business card, our method firstly extracts a document object region from a given image, and then classifies it into positive or negative class. In the step of extracting the document object region, a block-based processing is exploited to efficiently find the line segment candidates of its boundary, and RANSAC-like method under three constraints is used to search its real boundary. In classification step, after performing image normalization on the extracted region, the Fisher vector is extracted to represent the document object, then it is classified by linear-SVM. For evaluating the proposed method, we carry out some experiments by using the collected images, and show that our method has achieved about 94% accuracy.
引用
收藏
页码:393 / 402
页数:10
相关论文
共 13 条
[1]   Random forests [J].
Breiman, L .
MACHINE LEARNING, 2001, 45 (01) :5-32
[2]   Histograms of oriented gradients for human detection [J].
Dalal, N ;
Triggs, B .
2005 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOL 1, PROCEEDINGS, 2005, :886-893
[3]   USE OF HOUGH TRANSFORMATION TO DETECT LINES AND CURVES IN PICTURES [J].
DUDA, RO ;
HART, PE .
COMMUNICATIONS OF THE ACM, 1972, 15 (01) :11-&
[4]   RANDOM SAMPLE CONSENSUS - A PARADIGM FOR MODEL-FITTING WITH APPLICATIONS TO IMAGE-ANALYSIS AND AUTOMATED CARTOGRAPHY [J].
FISCHLER, MA ;
BOLLES, RC .
COMMUNICATIONS OF THE ACM, 1981, 24 (06) :381-395
[5]  
Hinton G.E., 2012, ARXIV, DOI DOI 10.9774/GLEAF.978-1-909493-38-4_2
[6]  
Jaakkola TS, 1999, ADV NEUR IN, V11, P487
[7]   Convolutional Neural Networks for Document Image Classification [J].
Kang, Le ;
Kumar, Jayant ;
Ye, Peng ;
Li, Yi ;
Doermann, David .
2014 22ND INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), 2014, :3168-3172
[8]   Structural similarity for document image classification and retrieval [J].
Kumar, Jayant ;
Ye, Peng ;
Doermann, David .
PATTERN RECOGNITION LETTERS, 2014, 43 :119-126
[9]   Robust detection of lines using the progressive probabilistic Hough transform [J].
Matas, J ;
Galambos, C ;
Kittler, J .
COMPUTER VISION AND IMAGE UNDERSTANDING, 2000, 78 (01) :119-137
[10]  
Nair V., 2010, ICML, P807, DOI DOI 10.5555/3104322.3104425