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논문 기본 정보

자료유형
학술저널
저자정보
Jeong Beom Park (Pai Chai University) Thomas Mandl (University of Hildesheim) Do Wan Kim (Pai Chai University)
저널정보
한국콘텐츠학회(IJOC) International JOURNAL OF CONTENTS International JOURNAL OF CONTENTS Vol.13 No.4
발행연도
2017.12
수록면
70 - 79 (10page)

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초록· 키워드

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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.

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ABSTRACT
1. INTRODUCTION
2. RELATED WORK
3. PROPOSED ALGORITHM
4. EXPEROMENTAL RESULTS
5. CONCLUSION
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