Browse > Article
http://dx.doi.org/10.5392/IJoC.2017.13.4.070

Patent Document Similarity Based on Image Analysis Using the SIFT-Algorithm and OCR-Text  

Park, Jeong Beom (Department of Information and Telecommunication Pai Chai University)
Mandl, Thomas (University of Hildesheim)
Kim, Do Wan (Pai Chai University)
Publication Information
International Journal of Contents / v.13, no.4, 2017 , pp. 70-79 More about this Journal
Abstract
Images are an important element in patents and many experts use images to analyze a patent or to check differences between patents. However, there is little research on image analysis for patents partly because image processing is an advanced technology and typically patent images consist of visual parts as well as of text and numbers. This study suggests two methods for using image processing; the Scale Invariant Feature Transform(SIFT) algorithm and Optical Character Recognition(OCR). The first method which works with SIFT uses image feature points. Through feature matching, it can be applied to calculate the similarity between documents containing these images. And in the second method, OCR is used to extract text from the images. By using numbers which are extracted from an image, it is possible to extract the corresponding related text within the text passages. Subsequently, document similarity can be calculated based on the extracted text. Through comparing the suggested methods and an existing method based only on text for calculating the similarity, the feasibility is achieved. Additionally, the correlation between both the similarity measures is low which shows that they capture different aspects of the patent content.
Keywords
Patent Similarity; Image Processing; Information Retrieval; Correlation Coefficient; SIFT; OpenIMAJ; OCR; Tess4j;
Citations & Related Records
연도 인용수 순위
  • Reference
1 P. Mandl, P. Womser-Hacker, Julia M. StruB, and Michael Schwantner, "Understanding trends in the patent domain," In Proceedings of the first international workshop on patent mining and its applications (ipamin 2014) co-located with konvens 2014, 2014.
2 A. Tiwari and V. Bansal, "Patseek: Content based image retrieval system for patent database," In The fourth international conference on electronic business (iceb), 2004, pp. 1167-1171.
3 C. A. Goncalves, C. T. Goncalves, R. Camacho, and E. C. Oliveira, "The impact of pre-processing on the classification of medline documents," In Pattern recognition in information systems(pris), 2010, pp. 53-61.
4 C. D. Manning, R. Raghavan, and H. Schutze, Introduction to informationretrieval, Cambridge University(Kyo-bo), 2008.
5 P. C. Gaigole, L. Patil, and P. Chaudhari, "Preprocessing techniques in text categorization," International Journal of Computer Applications(IJCA), no. 3, 2013, pp. 1-3.
6 S. Robertson, "Understanding inverse document frequency: on theoretical arguments for idf," Journal of documentation, vol. 60, no. 5, 2004, pp. 503-520.   DOI
7 T. Maintz, "Digital and medical image processing. Universiteit Utrecht," 2005, pp. 247-272. http://www.cs.uu.nl/docs/vakken/ibv/reader/readerINFOIBV.pdf (last retrieved : 01.09.2017)
8 D. G. Lowe, "Distinctive image features from scale-invariant keypoints," International journal of computer vision, vol. 60, no. 2, 2004, pp. 91-110.   DOI
9 M. Brown and D. G. Lowe, "Invariant features from interest point groups," In Bmvc., 2002.
10 C. Harris and M. Stephens, "A combined corner and edge detector," In Alvey vision conference, vol. 15, 1988, p. 50.
11 A. Singh, K. Bacchuwar, and A. Bhasin, "A survey of ocr applications," International Journal of Machine Learning and Computing, vol. 2, no. 3, 2012, p. 314.
12 R. Smith, "An overview of the tesseract ocr engine," Institute of Electrical and Electronics Engineers(IEEE), vol. 2, 2007, pp. 629-633.
13 S. Vrochidis, "Papadopoulos, Symeon; Moumtzidou, Anastasia; Sidiropoulos, Panagiotis; Pianta, Emanuelle; Kompatsiaris, Ioannis (2010): Towards Content-based Patent Image Retrieval. A Framework Perspective," World Patent Information, vol. 32, no. 2, 2010, pp. 94-106.   DOI
14 H. Ni, Z. Guo, and B. Huang, "Binary Patent Image Retrieval Using the Hierarchical Oriented Gradient Histogram," In: Proceedings of the International Conference on Service Science, ICSS, Weihai, China, May. 8-9 May, IEEE, 2015, pp. 23-27.
15 D. Liparas, A. Moumtzidou, S. Vrochidis, and I. Kompatsiaris, "Concept-oriented Labelling of Patent Images Based on Random Forests and Proximity-driven Generation of Synthetic Data," In: Proceedings of the 25th International Conference on Computational Linguistics. COLIN. Dublin, Ireland, Aug. 23-29, 2014, pp. 25-32.
16 S. Vrochidis, A. Moumtzidou, and I. Kompatsiaris, "Concept-based Patent Image Retrieval," In: World Patent Information, vol. 34, no. 4, 2012, pp. 292-303. DOI: 10.1016/j.wpi.2012.07.002   DOI
17 N. Bhatti and A. Hanbury, "Image search in patents," A review In: IJDAR, vol. 16, no. 4, 2013, pp. 309-329. DOI: 0.1007/s10032-012-0197-5   DOI
18 Arnaud Le Hors, Philippe Le Hegaret, Lauren Wood, Gavin Nicol, Jonathan Robie, Mike Champion, and Steve Byrne, "Document object model (dom) level 3 core specification," World Wide Web Consortium, 2004. http://travesia.mcu.es/portalnb/jspui/bitstream/10421/7473/1/DOM3-Core.pdf.(last retrieved : 01.09.2017)
19 E. J. Sarver and D. R. Sanders, "Aspheric, astigmatic, multifocal contact lens with asymmetric point spread function," Google Patents (US Patent App. 13/237,617), Feb. 9, 2012.
20 GridlogicsTechnologies, Contact lenses technology insight report, Patent iNSHIGHT Pro., 2014.
21 WIPO, "Standard st. 36," World Intellectual Property Organization(WIPO), 2007. http://www.wipo.int/export/sites/www/standards/en/pdf/03-36-01.pdf (last retrieved : 01.0917)
22 P. Chakraborty and A. Mallik, "An open source tesseract based tool for extracting text from images with application in braille translation for the visually impaired," International Journal of Computer Applications, vol. 68, no. 16, 2013.
23 K. EL GAJOUI, F. A. ALLAH, and M. OUMSIS, "Training tesseract tool for amazigh ocr," In Recent researches in applied computer science: Proceedings of the 15th international conference on applied computer science 2015, pp. 20-22.
24 D. F. Broderick, A. T. Foppe, J. Santilli, and R. C. Tucker, "Method and system for or dering customized cosmetic contact lenses," Google Patents (US Patent 6,746,120), Jun. 2004.
25 A. Sozykin and T. Epanchintsev, "Mipr-a framework for distributed image processing using hadoop," In Application of information and communication technologies (aict), 2015 9th international conference on, 2015, pp. 35-39.
26 H. Jonathon, S. Sina, and D. David, "The openimaj tutorial," 2012, http://openimaj.org/tutorial-pdf.pdf (last retrieved : 01.09.2017)
27 C. Im, Text classification for patents : Experiments with unigrams, bigrams and different weighting methods, Unpublished master's thesis, Paichai University and Hildesheim University, 2016.
28 G. Kondrak, "N-gram similarity and distance," In International symposium on string processing and information retrieval, 2005, pp. 115-126.
29 E. Keogh and A. Mueen, "Curse of dimensionality," In Encyclopedia of machine learning, Springer, 2011, pp. 257-258.
30 E. D'hondt, S. Verberne, C. Koster, and L. Boves, "Text representations for patent classification," Computational Linguistics, vol. 39, no. 3, 2013, pp. 755-775.   DOI
31 K. Toutanova, D. Klein, C. D. Manning, and Y. Singer, "Feature-rich part-ofspeech tagging with a cyclic dependency network," In Proceedings of the 2003 conference of the north american chapter of the association for computational linguistics on human language technology, vol. 1, 2003, pp. 173-180.
32 Anjali Ganesh Jivani, "A comparative study of stemming algorithms," International Journal of Computer Technology and Applications(IJCTA), vol. 2, no. 6, 2011, pp. 1930-1938.
33 C. Shalizi, "Stochastic processes (advanced probability ii)," Carnegie Mellon Univerity, 2006, pp. 189-196. http://www.stat.cmu.edu/_cshalizi/754/2006/notes/lecture-28.pdf (last retrieved : 01.09.2017)
34 M. Mukaka, "A guide to appropriate use of correlation coefficient in medical research," Malawi Medical Journal, vol. 24, no. 3, 2012, pp. 69-71.
35 G. Csurka, J. M. Renders, and G. Jacquet, "Xrce's participation at patent image classification and image-based patent retrieval tasks of the clef-ip 2011," In The conference and labs of the evaluation forum - intellectual property(clefip), 2011.
36 WIPO, "What is intellectual property?," World Intellectual Property Organization(WIPO), 2011. http://www.wipo.int/edocs/pubdocs/en/intproperty/450/wipo_pub_450.pdf (last retrieved : 01.0917)
37 H. Joho, L. A. Azzopardi, and W. Vanderbauwhede, "A survey of patent users: an analysis of tasks, behavior, search functionality and system requirements," In Proceedings of the third symposium on information interaction in context, 2010, pp. 13-24.
38 F. Piroi, M. Lupu, A. Hanbury, and V Zenz, "Clef-ip 2011: Retrieval in the intellectual property domain," In The conference and labs of the evaluation forum - intellectual property(clef-ip), 2011.
39 A. Hanbury, N. Bhatti, M. Lupu, and R. Morzinger, "Patent image retrieval: a survey," In Proceedings of the 4th workshop on patent information retrieval, 2011, pp. 3-8.