• Title/Summary/Keyword: Region-Based Method

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Design and Implementation of a Real-time Region Pointing System using Arm-Pointing Gesture Interface in a 3D Environment

  • Han, Yun-Sang;Seo, Yung-Ho;Doo, Kyoung-Soo;Choi, Jong-Soo
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.290-293
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    • 2009
  • In this paper, we propose a method to estimate pointing region in real-world from images of cameras. In general, arm-pointing gesture encodes a direction which extends from user's fingertip to target point. In the proposed work, we assume that the pointing ray can be approximated to a straight line which passes through user's face and fingertip. Therefore, the proposed method extracts two end points for the estimation of pointing direction; one from the user's face and another from the user's fingertip region. Then, the pointing direction and its target region are estimated based on the 2D-3D projective mapping between camera images and real-world scene. In order to demonstrate an application of the proposed method, we constructed an ICGS (interactive cinema guiding system) which employs two CCD cameras and a monitor. The accuracy and robustness of the proposed method are also verified on the experimental results of several real video sequences.

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Region Merging Method Preserving Object Boundary for Color Image Segmentation (칼라 영상 분할을 위한 경계선 보존 영역 병합 방법)

  • 유창연;곽내정;김영길;안재형
    • Journal of Korea Multimedia Society
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    • v.7 no.3
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    • pp.319-326
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    • 2004
  • In this paper, we propose color image segmentation by region merging method preserving the boundary of an object. The proposed method selects initial region by using quantized image's index map after vector quantizing an original image. After then, we merge regions by applying boundary restricted factor in order to consider the boundary of an object in HSI color space. Also we merge the regions in RGB color space for non-processed regions in HSI color space. And we reduce processing time by decreasing iterative process in region merging algorithm. Experimental results have demonstrated the superiority in region's segmentation results and processing time for various images.

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Tolerance-based Point Classification Algorithm for a Polygonal Region (공차를 고려한 다각형 영역의 내외부 판별 알고리즘)

  • 정연찬;박준철
    • Korean Journal of Computational Design and Engineering
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    • v.7 no.2
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    • pp.75-80
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    • 2002
  • This paper details a robust and efficient algorithm for point classification with respect to a polygon in 2D real number domain. The concept of tolerance makes this algorithm robust and consistent. It enables to define‘on-boundary’ , which can be interpreted as either‘in-’or‘out-’side region, and to manage rounding errors in floating point computation. Also the tolerance is used as a measure of reliability of point classifications. The proposed algorithm is based on a ray-intersection technique known as the most efficient, in which intersections between a ray originating from a given test point and the boundary of a region are counted. An odd number of intersections indicates that the point is inside region. For practical examples the algorithm is most efficient because most edges of the polygon region are processed by simple bit operations.

Hand Raising Pose Detection in the Images of a Single Camera for Mobile Robot (주행 로봇을 위한 단일 카메라 영상에서 손든 자세 검출 알고리즘)

  • Kwon, Gi-Il
    • The Journal of Korea Robotics Society
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    • v.10 no.4
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    • pp.223-229
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    • 2015
  • This paper proposes a novel method for detection of hand raising poses from images acquired from a single camera attached to a mobile robot that navigates unknown dynamic environments. Due to unconstrained illumination, a high level of variance in human appearances and unpredictable backgrounds, detecting hand raising gestures from an image acquired from a camera attached to a mobile robot is very challenging. The proposed method first detects faces to determine the region of interest (ROI), and in this ROI, we detect hands by using a HOG-based hand detector. By using the color distribution of the face region, we evaluate each candidate in the detected hand region. To deal with cases of failure in face detection, we also use a HOG-based hand raising pose detector. Unlike other hand raising pose detector systems, we evaluate our algorithm with images acquired from the camera and images obtained from the Internet that contain unknown backgrounds and unconstrained illumination. The level of variance in hand raising poses in these images is very high. Our experiment results show that the proposed method robustly detects hand raising poses in complex backgrounds and unknown lighting conditions.

Salient Region Extraction based on Global Contrast Enhancement and Saliency Cut for Image Information Recognition of the Visually Impaired

  • Yoon, Hongchan;Kim, Baek-Hyun;Mukhriddin, Mukhiddinov;Cho, Jinsoo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.5
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    • pp.2287-2312
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    • 2018
  • Extracting key visual information from images containing natural scene is a challenging task and an important step for the visually impaired to recognize information based on tactile graphics. In this study, a novel method is proposed for extracting salient regions based on global contrast enhancement and saliency cuts in order to improve the process of recognizing images for the visually impaired. To accomplish this, an image enhancement technique is applied to natural scene images, and a saliency map is acquired to measure the color contrast of homogeneous regions against other areas of the image. The saliency maps also help automatic salient region extraction, referred to as saliency cuts, and assist in obtaining a binary mask of high quality. Finally, outer boundaries and inner edges are detected in images with natural scene to identify edges that are visually significant. Experimental results indicate that the method we propose in this paper extracts salient objects effectively and achieves remarkable performance compared to conventional methods. Our method offers benefits in extracting salient objects and generating simple but important edges from images containing natural scene and for providing information to the visually impaired.

Microscopic Image-based Cancer Cell Viability-related Phenotype Extraction (현미경 영상 기반 암세포 생존력 관련 표현형 추출)

  • Misun Kang
    • Journal of Biomedical Engineering Research
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    • v.44 no.3
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    • pp.176-181
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    • 2023
  • During cancer treatment, the patient's response to drugs appears differently at the cellular level. In this paper, an image-based cell phenotypic feature quantification and key feature selection method are presented to predict the response of patient-derived cancer cells to a specific drug. In order to analyze the viability characteristics of cancer cells, high-definition microscope images in which cell nuclei are fluorescently stained are used, and individual-level cell analysis is performed. To this end, first, image stitching is performed for analysis of the same environment in units of the well plates, and uneven brightness due to the effects of illumination is adjusted based on the histogram. In order to automatically segment only the cell nucleus region, which is the region of interest, from the improved image, a superpixel-based segmentation technique is applied using the fluorescence expression level and morphological information. After extracting 242 types of features from the image through the segmented cell region information, only the features related to cell viability are selected through the ReliefF algorithm. The proposed method can be applied to cell image-based phenotypic screening to determine a patient's response to a drug.

Maritime region segmentation and segment-based destination prediction methods for vessel path prediction (선박 이동 경로 예측을 위한 해상 영역 분할 및 영역 단위 목적지 예측 방법)

  • Kim, Jonghee;Jung, Chanho;Kang, Dokeun;Lee, Chang Jin
    • Journal of IKEEE
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    • v.24 no.2
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    • pp.661-664
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    • 2020
  • In this paper, we propose a maritime region segmentation method and a segment-based destination prediction method for vessel path prediction. In order to perform maritime segmentation, clustering on destination candidates generated from the past paths is conducted. Then the segment-based destination prediction is followed. For destination prediction, different prediction methods are applied according to whether the current region is linear or not. In the linear domain, the vessel is regarded to move constantly, and linear prediction is applied. In the nonlinear domain with an uncertainty, we assume that the vessel moves similarly to the most similar past path. Experimental results show that applying the linear prediction and the prediction method using a similar path differently depending on the linearity and the uncertainty of the path is better than applying one of them alone.

Multi-scale crack detection using decomposition and composition (해체와 구성을 이용한 다중 스케일 균열 검출)

  • Kim, Young Ro;Chung, Ji Yung
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.9 no.3
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    • pp.13-20
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    • 2013
  • In this paper, we propose a multi-scale crack detection method. This method uses decomposition, composition, and shape properties. It is based on morphology algorithm, crack features. We use a morphology operator which extracts patterns of crack. It segments cracks and background using opening and closing operations. Morphology based segmentation is better than existing integration methods using subtraction in detecting a crack it has small width. However, morphology methods using only one structure element could detect only fixed width crack. Thus, we use decomposition and composition methods. We use a decimation method for decomposition. After decomposition and morphology operation, we get edge images given by binary values. Our method calculates values of properties such as the number of pixels and the maximum length of the segmented region. We decide whether the segmented region belongs to cracks according to those data. Experimental results show that our proposed multi-scale crack detection method has better results than those of existing detection methods.

A Global Optimization Algorithm Based on the Extended Domain Elimination Method (영역 제거법의 확장을 통한 전체 최적화 알고리듬 개선)

  • O, Seung-Hwan;Lee, Byeong-Chae
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.24 no.1 s.173
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    • pp.240-249
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    • 2000
  • An improved global optimization algorithm is developed by extending the domain elimination method. The concept of triangular patch consists of two or more trajectories of local minimizations is introduced to widen the attraction region of the domain elimination method. Using the an-]c between each of three vertices of the patch and a design point, we measure the proximity, between the design point and the patch. With the Gram-Schimidt orthonormalization, this method can be extended to general n-dimensional problems. We code the original domain elimination algorithm and a patch-based algorithm. Then we compare the performance of two algorithms. Through the well-known example problems. the algorithm using patch is shown to be superior to the original domain elimination algorithm in view of computational efficiency.

A New Scanning Method for MPEG-4 AVC based Fine Granular Scalable Video Coding (MPEG-4 AVC 기반 미세입자 스케일러블 비디오 코딩을 위한 새로운 스캔 방법)

  • 정원식;박광훈;김규헌
    • Journal of Broadcast Engineering
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    • v.7 no.4
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    • pp.345-354
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    • 2002
  • In this paper, we introduce a new scanning method for MPEG-4 AVC based Fine Granular Scalable video coding that can significantly improve the subjective picture quality of a decoded scalable video. The proposed scanning method can guarantee the subjectively improved picture qualify of the decoded scalable video by encoding, transmitting and decoding the visually important region most-preferentially. From the simulation results, it has been found that the proposed scanning method can lead the FGS method to achieve significantly improved picture quality, especially on the region of interests.