• Title/Summary/Keyword: 영상 전처리

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Comparisons of MPEG-7 Texture Descriptors for Iris recognition (MPEG-7 텍스쳐 서술자의 홍채 인식에 대한 성능 비교)

  • Choo, Hyon-Gon;Kim, Whoi-Yul
    • The KIPS Transactions:PartB
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    • v.11B no.4
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    • pp.421-428
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    • 2004
  • There are three texture descriptors in MPEG-7 : Homogeneous Texture, Edge Histogram and Texture Browsing. In this paper, a comparative analysis is presented on the capability of MPEG-7 texture descriptors for iris recognition as part of an MPEG-7 application using descriptors. Through the experiments of comparing the clustering efficiency and error distribution of the descriptors using 560 iris images, their discriminating capabilities for different iris groups are analyzed. The results show that Homogenous Texture descriptor is the best discriminator among three descriptors to recognize the iris pattern. However, compared with the conventional iris recognition methods, it needs more efforts to enhance the results.

Fully Automatic Liver Segmentation Based on the Morphological Property of a CT Image (CT 영상의 모포러지컬 특성에 기반한 완전 자동 간 분할)

  • 서경식;박종안;박승진
    • Progress in Medical Physics
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    • v.15 no.2
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    • pp.70-76
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    • 2004
  • The most important work for early detection of liver cancer and decision of its characteristic and location is good segmentation of a liver region from other abdominal organs. This paper proposes a fully automatic liver segmentation algorithm based on the abdominal morphology characteristic as an easy and efficient method. Multi-modal threshold as pre-processing is peformed and a spine is segmented for finding morphological coordinates of an abdomen. Then the liver region is extracted using C-class maximum a posteriori (MAP) decision and morphological filtering. In order to estimate results of the automatic segmented liver region, area error rate (AER) and correlation coefficients of rotational binary region projection matching (RBRPM) are utilized. Experimental results showed automatic liver segmentation obtained by the proposed algorithm provided strong similarity to manual liver segmentation.

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Effects of Tempering Temperature and Time on the Slip Melting Point of Fats (처리 온도 및 시간이 고형 유지의 상승 융점에 미치는 영향)

  • Yi, Young-Soo;Chang, Young-Sang;Shin, Zae-Ik
    • Korean Journal of Food Science and Technology
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    • v.23 no.1
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    • pp.19-24
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    • 1991
  • Among the conditions changes for the slip melting point of tempering temperature and time were studied. The results were treated below at $4^{\circ}C$, slip M.P. were not effected by tempering time. But slip M.P. of lard and palm oil had fallen treated at $10^{\circ}C$, the reason was that low melting triglycerides did not form the perfect crystals. Therefore, in order to measure the slip M.P. should be decrease the free energy and from stable crystallization of fats. Recommendable tempering temperature was treated at $4^{\circ}C$.

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$L_2$-Norm Pyramid--Based Search Algorithm for Fast VQ Encoding (고속 벡터 양자 부호화를 위한 $L_2$-평균 피라미드 기반 탐색 기법)

  • Song, Byeong-Cheol;Ra, Jong-Beom
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.1
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    • pp.32-39
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    • 2002
  • Vector quantization for image compression needs expensive encoding time to find the closest codeword to the input vector. This paper proposes a search algorithm for fast vector quantization encoding. Firstly, we derive a robust condition based on the efficient topological structure of the codebook to dramatically eliminate unnecessary matching operations from the search procedure. Then, we Propose a fast search algorithm using the elimination condition. Simulation results show that with little preprocessing and memory cost, the encoding time of the proposed algorithm is reduced significantly while the encoding quality remains the same with respect to the full search algorithm. It is also found that the Proposed algorithm outperforms the existing search algorithms.

Scene Change Detection and Representative Frame Extraction Algorithm for Video Abstract on MPEG Video Sequence (MPEG 비디오 시퀀스에서 비디오 요약을 위한 장면 전환 검출 및 대표 프레임 추출 알고리즘)

  • 강응관
    • Journal of Korea Multimedia Society
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    • v.6 no.5
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    • pp.797-804
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    • 2003
  • Scene change detection algorithm, which is very important preprocessing technique for video indexing and retrieval and determines the performance of video database system, is being studied widely. In this paper, we propose a more effective abrupt scene change detection, which is robust to large motion, sudden change of light and successive abrupt shot transitions rapidly. And we also propose a new gradual scene change detection algorithm, which can detect dissolve, and fade in/out precisely. Furthermore, we also propose a representative frame extraction algorithm which performs content-based video summary by novel DCT DC image buffering technique and accumulative histogram intersection measure (AHIM).

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A Study on the Number Recognition using Cellular Neural Network (Cellular Neural Network을 이용한 숫자인식에 관한 연구)

  • 전흥우;김명관;정금섭
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.6
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    • pp.819-826
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    • 2002
  • Cellular neural networks(CNN) are neural networks that have locally connected characteristics and real-time image processing. Locally connected characteristics are suitable for VLSI implementation. It also has applications in such areas as image processing and pattern recognition. In this thesis cellular neural networks are used for feature detection in number recognition at the stage of re-processing. The four or six directional shadow detectors are used in numbers recognition. At the stage of classification, this result of feature detection was simulated by using a multi-layer back Propagation neural network. The experiments indicate that the CNN feature detectors capture good features for number recognition tasks.

Feature Area-based Vehicle Plate Recognition System(VPRS) (특징 영역 기반의 자동차 번호판 인식 시스템)

  • Jo, Bo-Ho;Jeong, Seong-Hwan
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.6
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    • pp.1686-1692
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    • 1999
  • This paper describes the feature area-based vehicle plate recognition system(VPRS). For the extraction of vehicle plate in a vehicle image, we used the method which extracts vehicle plate area from a s vehicle image using intensity variation. For the extraction of the feature area containing character from the extracted vehicle plate, we used the histogram-based approach and the relative location information of individual characters in the extracted vehicle plate. The extracted feature area is used as the input vector of ART2 neural network. The proposed method simplifies the existing complex preprocessing the solves the problem of distortion and noise in the binarization process. In the difficult cases of character extraction by binarization process of previous method, our method efficiently extracts characters regions and recognizes it.

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CS-RANSAC Algorithm using Machine Learning Technique (머신러닝 기법올 적용한 CS-RANSAC 알고리즘)

  • Ko, Seunghyun;Yoon, Ui-Nyoung;Alikhanov, Jumabek;Jo, Geun-Sik
    • Annual Conference of KIPS
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    • 2016.10a
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    • pp.632-635
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    • 2016
  • 증강현실에서 영상과 증강된 콘텐츠 간의 이질감을 줄이기 위해서 정확한 호모그래피 행렬을 추정해야 하며, 정확한 호모그래피 행렬을 추정할때 RANSAC 알고리즘이 널리 사용된다. 그러나 RANSAC 알고리즘은 랜덤 샘플링 과정을 반복적으로 거치기 때문에 불필요한 연산 과정이 발생하고 이로 인해 알고리즘의 효율이 저하된다. 이러한 단점을 극복하기 위해 DCS-RANSAC 알고리즘이 제안되었다. 제안된 DCS-RANSAC 알고리즘은 이미지를 특징점 분포 패턴에 따라 그룹으로 분류하고 각 그룹에 제약조건 문제를 적용하여 불필요한 연산 과정을 줄이고 정확도를 향상시킨 알고리즘이다. 그러나 DCS-RANSAC 알고리즘에서 사용된 이미지 그룹 데이터는 수동적인 방법을 통해 직관적으로 분류되어 있지만 특징점 분포 패턴이 다양하지 않아 분류시 정확도가 저하되는 경우가 있다. 위의 문제점을 해결하기 위해 본 논문에서는 머신러닝 기법을 통해 이미지들을 자동으로 분류하고 각 그룹마다 각기 다른 제약조건을 적용하는 MCS-RANSAC 알고리즘을 제안한다. 제안하는 알고리즘은 머신러닝 기법을 사용하여 전처리 단계에서 이미지를 분류하고 분류된 이미지에 제약조건을 적용시켜 알고리즘의 처리시간을 줄이고 정확도를 향상시켰다. 실험 결과 본 논문에서 제안하는 MCS-RANSAC은 DCS-RANSAC 알고리즘에 비해 수행시간이 약 6% 단축되었고 호모그래피 오차율은 약 15% 줄어들었으며 참정보 비율은 2.8% 증가한 것으로 확인되었다.

An Approach to Segmentation of Address Strings of unconstrained handwritten Hangul using Run-Length Code (Rum-Length code를 이용한 제약없이 쓰여진 한글 필기체 주소열 분할)

  • Kim, Gyeonghwan;Yoon, Jason-J
    • Journal of KIISE:Software and Applications
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    • v.28 no.11
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    • pp.813-821
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    • 2001
  • While recognition of isolated units of writing, such as a character or a word, has been extensively studied, emphasis on the segmentation itself has been lacking. In this paper we propose an active segmentation method for handwritten Hangul address strings based on the Run-length code. A slant correction algorithm, which is considered as an important preprocessing step for the segmentation, is presented. Three fundamental candidate estimation functions are introduced to detect the clues on touching points, and the classification of touching types is attempted depending on the structural peculiarity of Hangul. Our experiments show segmentation performance of 88.2% on touching characters with minimal over-segmentation.

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Bilateral Symmetry Averaging and Simple Regression Analysis for Robust Face Detection Against Illumination Variation (조명 변화에 강인한 얼굴 검출을 위한 좌우대칭 평균화와 단순회귀분석 보정기법)

  • Cho, Chi-Young;Kim, Soo-Hwan
    • The Journal of the Korea Contents Association
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    • v.6 no.12
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    • pp.21-28
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    • 2006
  • In a face detection system based on template matching, histogram equalization or log transform is applied to an input image for the intensity normalization and the image improvement. It is known that they are noneffective in improving an image with intensity distortion by illumination variation. In this paper, we propose an efficient image improvement method using a simple regression analysis combined with a bilateral symmetry average for images with intensity distortion by illumination variation. Experimental results show that our method delivers the detection performance better than previous methods and also remarkably reduces the number of face candidates.

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