• Title/Summary/Keyword: Document Recognition

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A Query-by-Speech Scheme for Photo Albuming (음성 질의 기반 디지털 사진 검색 기법)

  • Kim Tae-Sung;Suh Young-Joo;Lee Yong-Ju;Kim Hoi-Rin
    • MALSORI
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    • no.57
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    • pp.99-112
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    • 2006
  • In this paper, we introduce two retrieval methods for photos with speech documents. We compare the pattern of speech query with those of speech documents recorded in digital cameras, and measure the similarities, and retrieve photos corresponding to the speech documents which have high similarity scores. As the first approach, a phoneme recognition scheme is used as the pre-processor for the pattern matching, and in the second one, the vector quantization (VQ) and the dynamic time warping (DTW) are applied to match the speech query with the documents in signal domain itself. Experimental results show that the performance of the first approach is highly dependent on that of phoneme recognition while the processing time is short. The second method provides a great improvement of performance. While the processing time is longer than that of the first method due to DTW, but we can reduce it by taking approximated methods.

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A Secure Face Cryptogr aphy for Identity Document Based on Distance Measures

  • Arshad, Nasim;Moon, Kwang-Seok;Kim, Jong-Nam
    • Journal of Korea Multimedia Society
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    • v.16 no.10
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    • pp.1156-1162
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    • 2013
  • Face verification has been widely studied during the past two decades. One of the challenges is the rising concern about the security and privacy of the template database. In this paper, we propose a secure face verification system which generates a unique secure cryptographic key from a face template. The face images are processed to produce face templates or codes to be utilized for the encryption and decryption tasks. The result identity data is encrypted using Advanced Encryption Standard (AES). Distance metric naming hamming distance and Euclidean distance are used for template matching identification process, where template matching is a process used in pattern recognition. The proposed system is tested on the ORL, YALEs, and PKNU face databases, which contain 360, 135, and 54 training images respectively. We employ Principle Component Analysis (PCA) to determine the most discriminating features among face images. The experimental results showed that the proposed distance measure was one the promising best measures with respect to different characteristics of the biometric systems. Using the proposed method we needed to extract fewer images in order to achieve 100% cumulative recognition than using any other tested distance measure.

A Study on Implementation of Printed Character Recognition System And Performance Evaluation (인쇄체 문자 인식기의 성능 평가에 관한 연구)

  • Kim, Min-Soo;Kang, Eun-Young;Kim, Eun-Young;Han, Sun-Hwa;Kim, Jin-Hyung
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.11
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    • pp.3584-3591
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    • 2000
  • In this paper we propose measure for performance evaluationof character recognition, We used three commercial character recognizers and one laboratory character recognizer for test. The characteristics of each recognizer is compared by proposed evaluation standrd, and analyzed characteristrics For the input test data, KT test collection are used. KT test collection is composed of 1000 document images about and complete source text. In this paper we propose method for measuring recognition rage in character unit for evaluation of character recogrition, The recogrition rates are compared and analyzed by single feature characteristic or mixed feature characteristic.

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Improved Edge Detection Algorithm Using Ant Colony System (개미 군락 시스템을 이용한 개선된 에지 검색 알고리즘)

  • Kim In-Kyeom;Yun Min-Young
    • The KIPS Transactions:PartB
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    • v.13B no.3 s.106
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    • pp.315-322
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    • 2006
  • Ant Colony System(ACS) is easily applicable to the traveling salesman problem(TSP) and it has demonstrated good performance on TSP. Recently, ACS has been emerged as the useful tool for the pattern recognition, feature extraction, and edge detection. The edge detection is wifely utilized in the area of document analysis, character recognition, and face recognition. However, the conventional operator-based edge detection approaches require additional postprocessing steps for the application. In the present study, in order to overcome this shortcoming, we have proposed the new ACS-based edge detection algorithm. The experimental results indicate that this proposed algorithm has the excellent performance in terms of robustness and flexibility.

Voice Activity Detection Algorithm using Wavelet Band Entropy Ensemble Analysis in Car Noisy Environments (문서 편집 접근성 향상을 위한 음성 명령 기반 모바일 어플리케이션 개발)

  • Park, Joo Hyun;Park, Seah;Lee, Muneui;Lim, Soon-Bum
    • Journal of Korea Multimedia Society
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    • v.21 no.11
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    • pp.1342-1352
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    • 2018
  • Voice Command systems are important means of ensuring accessibility to digital devices for use in situations where both hands are not free or for people with disabilities. Interests in services using speech recognition technology have been increasing. In this study, we developed a mobile writing application using voice recognition and voice command technology which helps people create and edit documents easily. This application is characterized by the minimization of the touch on the screen and the writing of memo by voice. We have systematically designed a mode to distinguish voice writing and voice command so that the writing and execution system can be used simultaneously in one voice interface. It provides a shortcut function that can control the cursor by voice, which makes document editing as convenient as possible. This allows people to conveniently access writing applications by voice under both physical and environmental constraints.

The Biometric Signature Delegation Method with Undeniable Property (부인봉쇄 성질을 갖는 바이오메트릭 서명 위임 기법)

  • Yun, Sunghyun
    • Journal of Digital Convergence
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    • v.12 no.1
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    • pp.389-395
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    • 2014
  • In a biometric signature scheme, a user's biometric key is used to sign the document. It also requires the user be authenticated with biometric recognition method, prior to signing the document. Because the biometric recognition is launched every time the signature session started, it is not suitable for electronic commerce applications such as shopping malls where large number of documents to sign are required. Therefore, to commercialize biometric based signature schemes, the new proxy signature scheme is needed to ease the burden of the signer. In the proxy signature scheme, the signer can delegate signing activities to trustful third parties. In this study, the biometric based signature delegation method is proposed. The proposed scheme is suitable for applications where a lot of signing are required. It is consisted of biometric key generation, PKI based mutual authentication, signature generation and verification protocols.

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

  • Park, Jeong Beom;Mandl, Thomas;Kim, Do Wan
    • International Journal of Contents
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    • v.13 no.4
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    • pp.70-79
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    • 2017
  • 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.

A Study on the Application of Knowledge-based Service in Procurement Engineering (구매엔지니어링을 위한 지식기반 서비스 적용 방안에 관한 연구)

  • Kim, Jinil;Cha, Jaemin;Shin, Joonguk;Yeum, Choongseup
    • Journal of the Korean Society of Systems Engineering
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    • v.14 no.2
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    • pp.67-72
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    • 2018
  • In the EPC(Engineering Procurement and Construction) project of the plant, procurement engineering has a profound effect on the profitability of the project. It is important that the procurement specifications are well written to ensure that procurement engineering works properly. In the meantime, the procurement specifications have been created by the experience of the person in charge because there was no system for helping procurement engineering. To cope with this situation, we are developing a procurement engineering management support system (PeMSS). This paper describes how to implement a knowledge-based service in the procurement engineering management support system. First, we briefly introduce the PeMSS, the knowledge base application field, and how to apply it. The parts that requires knowledge-based service are parsing the requirements in the PDF (Portable Document Format) file and management of the document provided by the supplier of the equipment.

The Extraction of Table Lines and Data in Document Image (문서영상에서 표 구성 직선과 데이터 추출)

  • Jang, Dae-Geun;Kim, Eui-Jeong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.3
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    • pp.556-563
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    • 2006
  • We should extract lines and data which consist of the table in order to classify the table region and analyze its structure in document image. But it is difficult to extract lines and data exactly because the lines are cut and their lengths are changed, or characters or noises are merged to the table lines. These problems result from the error of image input device or image reduction. In this paper, we propose the better method of extracting lines and data for table region classification and structure analysis than the previous ones including commercial softwares. The prposed method extracts horizontal and vertical lines which consist of the table by the use of one dimensional median filter. This filter not only eliminates the noises which attach to the line and the lines which are orthogonal to the filtering direction, but also connects the cut line of which the gap is shorter than the length of the filter tap in the process of extracting lines to the filtering direction. Furthermore, texts attached to the line are separated in the process of extracting vertical lines. This is an example of ABSTRACT format.

Terminology Recognition System based on Machine Learning for Scientific Document Analysis (과학 기술 문헌 분석을 위한 기계학습 기반 범용 전문용어 인식 시스템)

  • Choi, Yun-Soo;Song, Sa-Kwang;Chun, Hong-Woo;Jeong, Chang-Hoo;Choi, Sung-Pil
    • The KIPS Transactions:PartD
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    • v.18D no.5
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    • pp.329-338
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    • 2011
  • Terminology recognition system which is a preceding research for text mining, information extraction, information retrieval, semantic web, and question-answering has been intensively studied in limited range of domains, especially in bio-medical domain. We propose a domain independent terminology recognition system based on machine learning method using dictionary, syntactic features, and Web search results, since the previous works revealed limitation on applying their approaches to general domain because their resources were domain specific. We achieved F-score 80.8 and 6.5% improvement after comparing the proposed approach with the related approach, C-value, which has been widely used and is based on local domain frequencies. In the second experiment with various combinations of unithood features, the method combined with NGD(Normalized Google Distance) showed the best performance of 81.8 on F-score. We applied three machine learning methods such as Logistic regression, C4.5, and SVMs, and got the best score from the decision tree method, C4.5.