• Title/Summary/Keyword: 텍스처 추출

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Efficient Image Retrieval for WebCAM Video (WebCAM 기반 Video 내에서의 효율적인 이미지 검색 기법)

  • 하근희;최정구;김도년;조동섭
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1997.10a
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    • pp.377-382
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    • 1997
  • 멀티미디어가 발달함에 딸 이를 위한 다양한 검색 기법들이 제안되고 있다. 본 논문에서는 WeCAM 시스템에서 비디오 검색을 하기 위한 텍스처 성분과 영상의 윤곽선 특징을 동시에 이용한 검색 기법을 제안한다. 텍스처 특성 추출에는 8$\times$8 블록 DCT를 기반으로한 DCT-par와 DCT-energy 기법을 적용하고 윤곽선 추출에는 DCT의 대각선 계수를 이용하는 기법을 이용한다. WebCAM으로 생성된 비디오는 MPEG표준을 따르는 것으로 가정하고 있으며, 압축된 데이터에 디코딩 과정없이 직접 검색 기법을 적용함으로써 처리 시간을 단축할수 있다는 장점이 있다.

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Texture Feature for Robust Particle Filter Based Face Tracking (파티클 필터에 기반한 강인한 얼굴추적을 위한 텍스처 특징 추출에 관한 연구)

  • Kim, Dongkyu;Lee, Seung Ho;Kim, Hyung-Il;Ro, Yong Man
    • Annual Conference of KIPS
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    • 2015.04a
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    • pp.878-880
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    • 2015
  • 파티클 필터 기반 얼굴추적은 비교적 빠른 속도와 구현의 용이성으로 널리 사용되고 있으나 조명이나 포즈변화가 있는 영상에서 드리프트(drift) 현상에 의해 얼굴추적의 정확도가 급격히 저하된다. 본 논문에서는 앞에 언급한 얼굴의 다양성에 강인한 얼굴 텍스처 특징을 제안한다. 제안방법은 인접한 픽셀들 간의 관계를 고려한 텍스처 패턴을 정의할 때 인접한 픽셀들의 평균(average)을 적용하여 조명변화에 강인하다. 또한 얼굴의 구조적 정보를 반영한 블록 기반의 텍스처 패턴 풀링(pooling)에 의해 포즈변화에 강인하다. 실제 감시환경을 가정해 CCTV 카메라로 자체 제작한 비디오 영상에서 Local Binary Pattern(LBP)와 같은 대표적인 특징들과 비교 실험을 수행하였다. 실험결과, 드리프트(drift) 폭이 적어 더 높은 얼굴추적 정확도를 보였으며 초당 28 프레임의 매우 빠른 처리속도를 보였다.

Cotent-based Image Retrieving Using Color Histogram and Color Texture (컬러 히스토그램과 컬러 텍스처를 이용한 내용기반 영상 검색 기법)

  • Lee, Hyung-Goo;Yun, Il-Dong
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.9
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    • pp.76-90
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    • 1999
  • In this paper, a color image retrieval algorithm is proposed based on color histogram and color texture. The representative color vectors of a color image are made from k-means clustering of its color histogram, and color texture is generated by centering around the color of pixels with its color vector. Thus the color texture means texture properties emphasized by its color histogram, and it is analyzed by Gaussian Markov Random Field (GMRF) model. The proposed algorithm can work efficiently because it does not require any low level image processing such as segmentation or edge detection, so it outperforms the traditional algorithms which use color histogram only or texture properties come from image intensity.

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The Classification Accuracy Improvement of Satellite Imagery Using Wavelet Based Texture Fusion Image (웨이브릿 기반 텍스처 융합 영상을 이용한 위성영상 자료의 분류 정확도 향상 연구)

  • Hwang, Hwa-Jeong;Lee, Ki-Won;Kwon, Byung-Doo;Yoo, Hee-Young
    • Korean Journal of Remote Sensing
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    • v.23 no.2
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    • pp.103-111
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    • 2007
  • The spectral information based image analysis, visual interpretation and automatic classification have been widely carried out so far for remote sensing data processing. Yet recently, many researchers have tried to extract the spatial information which cannot be expressed directly in the image itself. Using the texture and wavelet scheme, we made a wavelet-based texture fusion image which includes the advantages of each scheme. Moreover, using these schemes, we carried out image classification for the urban spatial analysis and the geological structure analysis around the caldera area. These two case studies showed that image classification accuracy of texture image and wavelet-based texture fusion image is better than that of using only raw image. In case of the urban area using high resolution image, as both texture and wavelet based texture fusion image are added to the original image, the classification accuracy is the highest. Because detailed spatial information is applied to the urban area where detail pixel variation is very significant. In case of the geological structure analysis using middle and low resolution image, the images added by only texture image showed the highest classification accuracy. It is interpreted to be necessary to simplify the information such as elevation variation, thermal distribution, on the occasion of analyzing the relatively larger geological structure like a caldera. Therefore, in the image analysis using spatial information, each spatial information analysis method should be carefully selected by considering the characteristics of the satellite images and the purpose of study.

Polygonal Model Simplification Method for Game Character (게임 캐릭터를 위한 폴리곤 모델 단순화 방법)

  • Lee, Chang-Hoon;Cho, Seong-Eon;Kim, Tai-Hoon
    • Journal of Advanced Navigation Technology
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    • v.13 no.1
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    • pp.142-150
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    • 2009
  • It is very important to generate a simplified model from a complex 3D character in computer game. We propose a new method of extracting feature lines from a 3D game character. Given an unstructured 3D character model containing texture information, we use model feature map (MFM), which is a 2D map that abstracts the variation of texture and curvature in the 3D character model. The MFM is created from both a texture map and a curvature map, which are produced separately by edge-detection to locate line features. The MFM can be edited interactively using standard image-processing tools. We demonstrate the technique on several data sets, including, but not limited to facial character.

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Brick Path Recognition Using Image Shape Pattern and Texture Feature (영상의 형태 패턴과 텍스처 특징을 이용한 보도블록의 인식방법)

  • Woo, Byung-Seok;Yang, Sung-Min;Jo, Kang-Hyun
    • Journal of Korea Multimedia Society
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    • v.15 no.4
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    • pp.472-484
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    • 2012
  • Raised or plain block is widely used for the pedestrian's safe passage. The insincere construction, insufficient maintenance and obstacle overlaid on the pavement cause pedestrian's accidents. This paper proposes a method to detect brick path by analyzing the shape pattern and texture feature of brick located in visible distance for a safe passage. A brick appears to a regular type because of its specific shape which repeats with its sized gap and its type varies according to the surrounding environment or use. This paper shows a method which extracts the shape pattern by analyzing single surface polygon and its frequency appearing in road area. The shape pattern is used to detect similar shape regions. Some regions are not detected because extraneous substances or chopped bricks distort the original shape. This problem can be solved by analyzing the texture feature vector. The analyzed vector of the previously detected regions yields the Gaussian distribution. This value in each undetected region is computed and checked whether it's satisfied with Gaussian distribution or not. The satisfied region is detected as the brick path. The experiment was performed with the various type's bricks to recognize so that the results showed as accurate as 95.9% in average.

Content-based Image Retrieval Using Multiple Filters (다중 필터를 이용한 내용기반 이미지 검색 기술)

  • 김상수;백성욱;조영기;조주상
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10b
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    • pp.709-711
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    • 2004
  • 이 논문의 목적은 기하급수적으로 늘어나고 있는 이미지 데이터의 효율적인 검색을 위해 텍스처의 특징을 추출하여 이미지를 검색하는 방법을 제시하고, 다중 필터를 이용한 이미지 검색 기술을 보여주는 것이다. 본 논문에서는 텍스처 이미지 분석에 다양하게 이용되고 있는 Gabor Filtering 기술을 이용하여 질의 이미지에 대한 최적 필터를 선택하는 과정과 선택된 필터를 적용하여 최적의 이미지를 검색하는 프로세스를 제시하고자 한다.

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Heterogeneous Face Recognition Using Texture feature descriptors (텍스처 기술자들을 이용한 이질적 얼굴 인식 시스템)

  • Bae, Han Byeol;Lee, Sangyoun
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.3
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    • pp.208-214
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    • 2021
  • Recently, much of the intelligent security scenario and criminal investigation demands for matching photo and non-photo. Existing face recognition system can not sufficiently guarantee these needs. In this paper, we propose an algorithm to improve the performance of heterogeneous face recognition systems by reducing the different modality between sketches and photos of the same person. The proposed algorithm extracts each image's texture features through texture descriptors (gray level co-occurrence matrix, multiscale local binary pattern), and based on this, generates a transformation matrix through eigenfeature regularization and extraction techniques. The score value calculated between the vectors generated in this way finally recognizes the identity of the sketch image through the score normalization methods.

Developing a Dynamic Selection Algorithm in Multiple Cameras (다중 카메라의 동적인 선택 알고리즘 개발)

  • Jang, Seok-Woo;Choi, Hyun-Jun;Lee, Suk-Yun
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2013.01a
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    • pp.223-225
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    • 2013
  • 본 논문에서는 카메라가 여러 개 존재하는 다중의 카메라 환경에서 주변의 환경에 최적으로 적합한 카메라를 동적으로 선택하는 알고리즘을 제안한다. 제안된 알고리즘에서는 초기의 입력영상을 받아들인 후, 이 영상으로부터 주위의 환경을 가장 잘 표현할 수 있는 특징인 밝기와 텍스처 특징을 추출한다. 그리고 이전 단계에서 추출된 밝기와 텍스처 특징값들을 가장 잘 반영할 수 있는 카메라를 선택하는 규칙을 생성함으로써 주위 환경에 맞는 카메라를 자동으로 선택해 준다. 본 논문의 실험결과에서는 제안된 방법이 여러 가지 환경에서 잘 동작하며, 결과적으로 주위 환경에 적합한 카메라의 선택을 통해 보다 정확한 3차원의 정보를 추출함을 보여준다.

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Rotation and Translation Invariant Feature Extraction Using Angular Projection in Frequency Domain (주파수 영역에서 각도 투영법을 이용한 회전 및 천이 불변 특징 추출)

  • Lee, Bum-Shik;Kim, Mun-Churl
    • Journal of the HCI Society of Korea
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    • v.1 no.2
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    • pp.27-33
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    • 2006
  • This paper presents a new approach to translation and rotation invariant feature extraction for image texture retrieval. For the rotation invariant feature extraction, we invent angular projection along angular frequency in Polar coordinate system. The translation and rotation invariant feature vector for representing texture images is constructed by the averaged magnitude and the standard deviations of the magnitude of the Fourier transform spectrum obtained by the proposed angular projection. In order to easily implement the angular projection, the Radon transform is employed to obtain the Fourier transform spectrum of images in the Polar coordinate system. Then, angular projection is applied to extract the feature vector. We present our experimental results to show the robustness against the image rotation and the discriminatory capability for different texture images using MPEG-7 data set. Our Experiment result shows that the proposed rotation and translation invariant feature vector is effective in retrieval performance for the texture images with homogeneity, isotropy and local directionality.

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