• Title/Summary/Keyword: illumination estimation

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Robust Visual Tracking using Search Area Estimation and Multi-channel Local Edge Pattern

  • Kim, Eun-Joon
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.7
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    • pp.47-54
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    • 2017
  • Recently, correlation filter based trackers have shown excellent tracking performance and computational efficiency. In order to enhance tracking performance in the correlation filter based tracker, search area which is image patch for finding target must include target. In this paper, two methods to discriminatively represent target in the search area are proposed. Firstly, search area location is estimated using pyramidal Lucas-Kanade algorithm. By estimating search area location before filtering, fast motion target can be included in the search area. Secondly, we investigate multi-channel Local Edge Pattern(LEP) which is insensitive to illumination and noise variation. Qualitative and quantitative experiments are performed with eight dataset, which includes ground truth. In comparison with method without search area estimation, our approach retain tracking for the fast motion target. Additionally, the proposed multi-channel LEP improves discriminative performance compare to existing features.

The Binarization of Text Regions in Natural Scene Images, based on Stroke Width Estimation (자연 영상에서 획 너비 추정 기반 텍스트 영역 이진화)

  • Zhang, Chengdong;Kim, Jung Hwan;Lee, Guee Sang
    • Smart Media Journal
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    • v.1 no.4
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    • pp.27-34
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    • 2012
  • In this paper, a novel text binarization is presented that can deal with some complex conditions, such as shadows, non-uniform illumination due to highlight or object projection, and messy backgrounds. To locate the target text region, a focus line is assumed to pass through a text region. Next, connected component analysis and stroke width estimation based on location information of the focus line is used to locate the bounding box of the text region, and each box of connected components. A series of classifications are applied to identify whether each CC(Connected component) is text or non-text. Also, a modified K-means clustering method based on an HCL color space is applied to reduce the color dimension. A text binarization procedure based on location of text component and seed color pixel is then used to generate the final result.

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Contour Shape Matching based Motion Vector Estimation for Subfield Gray-scale Display Devices (서브필드계조방식 디스플레이 장치를 위한 컨투어 쉐이프 매칭 기반의 모션벡터 추정)

  • Choi, Im-Su;Kim, Jae-Hee
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.327-328
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    • 2007
  • A contour shape matching based pixel motion estimation is proposed. The pixel motion information is very useful to compensate the motion artifact generated at the specific gray level contours in the moving image for subfield gray-scale display devices. In this motion estimation method, the gray level boundary contours are extracted from the input image. Then using contour shape matching, the most similar contour in next frame is found, and the contour is divided into segment unit. The pixel motion vector is estimated from the displacement of the each segment in the contour by segment matching. From this method, more precise motion vector can be estimated and this method is more robust to image motion with rotation or from illumination variations.

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Estimation of Spectral Distribution of Illumination Using Maximum Achromatic Region (최대 무채색 영역을 이용한 광원의 분광분포 추정)

  • Kim, Hui-Su;Kim, Yun-Tae;Lee, Cheol-Hui;Ha, Yeong-Ho
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.4
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    • pp.392-400
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    • 2001
  • This paper proposes an illuminant estimation algorithm that estimates the spectral power distribution of an incident light source from a single image. The proposed illumination recovery procedure has two phases. First, the surface spectral reflectances are recovered in the maximum achromatic region (MAR) which is the most achromatic and highly bright region of an image after removing partially the effect of illumination using a modified gray world algorithm. Here, the surface reflectances of MAR are estimated using the principal component analysis method along with a set of given 1269 Munsell samples. Second, the Population of reflected lights is determined with 1269 Munsell samples and a set of illuminations then the spectral distribution of re(looted lights of MAR is selected from the spectral database. That is, color differences are compared between the reflected lights of the MAR and the spectral database, which is the set of reflected lights built by the given set of Munsell samples and illuminants. Then the closest colors from the spectral database are selected. Finally, the illuminant of an image can be calculated dividing the average spectral distributions of reflected lights of MAR by the average surface reflectances of the MAR. In order to evaluate the proposed algorithm, experiments with artificial scenes, which are exposed to chromatic illuminants, were performed and the spectral distribution of estimated illumination and color difference are compared with results of the conventional method.

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Estimation of the 3-D Shape Surfaces with Specular Reflections

  • Kim, Jee Hong
    • Journal of the Optical Society of Korea
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    • v.18 no.6
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    • pp.672-678
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    • 2014
  • We propose a method to estimate the 3-D shape of surfaces with specular reflection, using a model of the difference in appearance between images reflected from a flat surface and a curved surface. First, we analyze the geometry of spatial reflection from a specular surface and how reflected light varies due to a curved surface. This is used to estimate 3-D shape. The proposed method is shown to be effective in experiments using illumination from spatially distributed light sources and a camera capturing the reflected light from curved, specular surfaces.

Application of PIV to Fluid-Machinery Studies (유체기계연구에서의 PIV의 적용)

  • Lee, Y. H.
    • 유체기계공업학회:학술대회논문집
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    • 1997.02a
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    • pp.188-195
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    • 1997
  • The application of PIV to the studies of fluid-machines, especially focused on turbo-machinery is reviewed by scrutinizing the previous investigation. Owing to the inevitable high-speed analysis of turbo-machinery consisting of rotating impellers, the importance of optical setups to cope with illumination problem is frequently mentioned as main ingredient affecting the PIV performance. And the acquisition of the relative velocity and absolute velocity is determined mainly by the optical recording conditions. A few studies cast satisfactory extension of the PIV data to quantitative pressure estimation and related noise assessment.

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Color Image Recovery using Image illumination Estimation (영상의 광원 추정을 이용한 칼라 영상 복원)

  • 안강식;안명석;조석제
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2000.08a
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    • pp.201-204
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    • 2000
  • 본 논문에서는 기존의 칼라 항상성(color constancy) 알고리즘을 기반으로 한 새로운 영상 복원 방법을 제안한다. 이 방법은 인간의 시각 특성을 선형 모델로 표현한 칼라 항상성 모델을 이용한다. 칼라 항상성 모델에서 가장 중요한 과정은 영상의 광원을 추정하는 것이다. 이론 위하여 영상에서 명도 값이 가장 큰 화소의 값을 이용하며, 이 값을 각 수광체(photoreceptor)의 응답으로 대체한다. 추정된 광원을 이용하여 만들어진 영상을 일정한 비율로 스케일링하여 영상을 복원한다. 실험을 통하여 제안한 항법으로 영상 복원이 잘 됨을 알 수 있었다.

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Localization of Mobile Robot Using Color Landmark mounted on Ceiling (천장 부착 컬러 표식을 이용한 이동로봇의 자기위치추정)

  • Oh, Jong-Kyu;Lee, Chan-Ho
    • Proceedings of the KIEE Conference
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    • 2001.11c
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    • pp.91-94
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    • 2001
  • In this paper, we proposed localization method of mobile robot using color landmark mounted on ceiling. This work is composed 2 parts : landmark recognition part which finds the position of multiple landmarks in image and identifies them and absolute position estimation part which estimates the location and orientation of mobile robot in indoor environment. In landmark recognition part, mobile robot detects artificial color landmarks using simple histogram intersection method in rg color space which is insensitive to the change of illumination. Then absolute position estimation part calculates relative position of the mobile robot to the detected landmarks. For the verification of proposed algorithm, ceiling-orientated camera was installed on a mobile robot and performance of localization was examined by designed artificial color landmarks. As the result of test, mobile robot could achieve the reliable landmark detection and accurately estimate the position of mobile robot in indoor environment.

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Schooling Behavior and Estimation of the Fish School in Set Net by Fish Finder (어군탐지기에 의한 정치망내의 어군의 행동과 어군량 추정)

  • 신형일
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.22 no.1
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    • pp.11-18
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    • 1986
  • Schooling behavier to a fishing gear and estimation of the volume of fish school in set net have ~ been studied by making use of such techniques as visual observations, underwater cameras, under- water televison. However, all of these observation techniques are subject to restrictions caused by illumination, underwater visibility, underwater transparent and sea conditions. For the above mentioned reasoa, one of the most effective method by this time become generally known a method using fish finder. In this paper, in order to control the fishing ground of set net effectively and to develope the telemetric fish finder, the experiments for the target strength, underwater shape of fishing gear, schooling behavier and volume of fish school with fish finder were performed at Galgott fishing ground of set net located Keouje Island, 15th-24th July and 18th-20th October in 1985. The results of these experiment showed that a method using fish finder in fishing grOlllld of set net is available for estimating distribution and school size, fish behavier in relation to a fishing gear and underwater shape of fishing gears.

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Enhancing Single Thermal Image Depth Estimation via Multi-Channel Remapping for Thermal Images (열화상 이미지 다중 채널 재매핑을 통한 단일 열화상 이미지 깊이 추정 향상)

  • Kim, Jeongyun;Jeon, Myung-Hwan;Kim, Ayoung
    • The Journal of Korea Robotics Society
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    • v.17 no.3
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    • pp.314-321
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    • 2022
  • Depth information used in SLAM and visual odometry is essential in robotics. Depth information often obtained from sensors or learned by networks. While learning-based methods have gained popularity, they are mostly limited to RGB images. However, the limitation of RGB images occurs in visually derailed environments. Thermal cameras are in the spotlight as a way to solve these problems. Unlike RGB images, thermal images reliably perceive the environment regardless of the illumination variance but show lacking contrast and texture. This low contrast in the thermal image prohibits an algorithm from effectively learning the underlying scene details. To tackle these challenges, we propose multi-channel remapping for contrast. Our method allows a learning-based depth prediction model to have an accurate depth prediction even in low light conditions. We validate the feasibility and show that our multi-channel remapping method outperforms the existing methods both visually and quantitatively over our dataset.