• Title/Summary/Keyword: boundary pixel

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Post-processing Technique based on POCS for visual Enhancement (POCS를 이용한 효과적인 블록 현상 제거 기법)

  • Kim, Yoon;Jung, Jae-Han;Kim, Jae-Won;Ko, Sung-Jea
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.755-758
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    • 2001
  • In this paper. Ive propose a postprocessing technique based on the theory of projection on convex sets(POCS) to reduce the blocking artifacts in HDTV decoded images. In BDCT of HDTV. the image is divided into a grid of non-overlapped 8 ${\times}$ 8 blocks. and then each block is coded separately. A block which is located one pixel apart from the grid of BDCT will include the boundary of the original 8 ${\times}$ 8 block. If the blocking artifact is Introduced alone the block boundary. this block will have different frequency characteristic from that of the original block. Thus, a comparison of frequency characteristics of these two overlapping blocks can detect the undesired high-frequency components mainly caused by the blocking artifact. By eliminating these undesired high-frequency components adaptively, robust smoothing projection operator can be obtained. Simulation results with real image sequences indicate that the proposed method performs better than conventional algorithms.

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Image Segmentation Using Level Set Method with New Speed Function (새로운 속도함수를 갖는 레벨 셋 방법을 이용한 의료영상분할)

  • Kim, Sun-Worl;Cho, Wan-Hyun
    • The Korean Journal of Applied Statistics
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    • v.24 no.2
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    • pp.335-345
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    • 2011
  • In this paper, we propose a new hybrid speed function for image segmentation using level set. A new proposed speed function uses the region and boundary information of image object for the exact result of segmentation. The region information is defined by the probability information of pixel intensity in a ROI(region-of-interest), and the boundary information is defined by the gradient vector flow obtained from the gradient of image. We show the results of experiment for an various artificial image and real medical image to verify the accuracy of segmentation using proposed method.

Fast Thumbnail Extraction Algorithm with Partial Decoding for HEVC (HEVC에서 부분복호화를 통한 썸네일 추출 알고리듬)

  • Lee, Wonjin;Jeong, Jechang
    • Journal of Broadcast Engineering
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    • v.23 no.3
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    • pp.431-436
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    • 2018
  • In this paper, a simple but effective algorithm to reduce the computational complexity of thumbnail generation and to improve image quality without aliasing artifacts is proposed. For the high speed decoding, the proposed algorithm performs partial decoding per $4{\times}4$ boundary in TU(Transform Unit), and preforms TU boundary in PU(Prediction Unit). The proposed method defines the weights based on intra prediction directions and estimates the thumbnail pixel by using that weights. this method remains thumbnail extraction time and improves thumbnail image quality compared with conventional algorithms.

A study on Iris Recognition using Wavelet Transformation and Nonlinear Function

  • Hur Jung-Youn;Truong Le Xuan;Lee Sang-Kyu
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.3
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    • pp.357-362
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    • 2005
  • Iris recognition system is the one of the most reliable biometries recognition system. An algorithm is proposed to determine the localized iris from the iris image received from iris input camera in client. For the first step, the algorithm determines the center of pupil. For the second step, the algorithm determines the outer boundary of the iris and the pupillary boundary. The localized iris area is transformed into polar coordinates. After performing three times Wavelet transformation, normalization was done using a sigmoid function. The converting binary process performs normalized value of pixel from 0 to 255 to be binary value, and then the converting binary process is compared pairs of two adjacent pixels. The binary code of the iris is transmitted to the server by the network. In the server, the comparing process compares the binary value of presented iris to the reference value in the database. The process of recognition or rejection is dependent on the value of Hamming Distance. After matching the binary value of presented iris with the database stored in the server, the result is transmitted to the client.

Line segment grouping method for building roof detection in aerial images (항공영상에서 건물지붕 검출을 위한 선소의 그룹화 기법)

  • Ye, Cheol-Su;Im, Yeong-Jae;Yang, Yeong-Gyu
    • 한국지형공간정보학회:학술대회논문집
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    • 2002.11a
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    • pp.133-140
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    • 2002
  • This paper presents a method for line segment grouping used for detection of various building roofs. First, by using edge preserving filtering. noise is eliminated and then images are segmented by watershed algorithm, which preserves location of edge pixels. To extract line segments between control points from boundary of each region, we calculate curvature of each pixel on the boundary and then find the control points. Line linking is performed according to direction and length of line segments and finally the location of line segments is adjusted using gradient magnitudes of all pixels of the line segment. The algorithm has been applied to aerial imagery and the results show accurate building roof detection.

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Efficient Transformations Between an $n^2$ Pixel Binary Image and a Boundary Code on an $n^3$ Processor Reconfigurable Mesh ($n^3$ 프로세서 재구성가능 메쉬에서 $n^2$ 화소 이진영상과 경계코드간의 효율적인 변환)

  • Kim, Myung
    • The Transactions of the Korea Information Processing Society
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    • v.5 no.8
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    • pp.2027-2040
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    • 1998
  • In this paper, we present efficient reconfigurable mesh algorithms for transforming between a binary image and its corresponding boundary code. These algorithms use $n\timesn\timesn$ processors when the size of the binary image is $n\timesn$. Recent published results show that these transformations can be done in O(1) time using $O(n^4)$ processors. The number of processors used by these algorithms is very large compared to the number of pixels in the image. Here, we present fast transformation algorithms which use $n^3 processors only. the transformation from a houndary code to a binary image takes O(1) time, and the converse transformation takes O(log n) time.

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Reconstruction of Color-Volume Data for Three-Dimensional Human Anatomic Atlas (3차원 인체 해부도 작성을 위한 칼라 볼륨 데이터의 입체 영상 재구성)

  • 김보형;이철희
    • Journal of Biomedical Engineering Research
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    • v.19 no.2
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    • pp.199-210
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    • 1998
  • In this paper, we present a 3D reconstruction method of color volume data for a computerized human atlas. Binary volume rendering which takes the advantages of object-order ray traversal and run-length encoding visualizes 3D organs at an interactive speed in a general PC without the help of specific hardwares. This rendering method improves the rendering speed by simplifying the determination of the pixel value of an intermediate depth image and applying newly developed normal vector calculation method. Moreover, we describe the 3D boundary encoding that reduces the involved data considerably without the penalty of image quality. The interactive speed of the binary rendering and the storage efficiency of 3D boundary encoding will accelerate the development of the PC-based human atlas.

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A Improved Equivalent Table Algorithm for Connected Region Labeling (연결 영역의 라벨링을 위한 동치테이블 개선 알고리즘)

  • Oh, Choonsuk
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.1
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    • pp.261-264
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    • 2019
  • There is the boundary following algorithm called by blob coloring or connected region labeling, which means that each pixel of the internal region can be filled with group label values by the raster scanning. This process represents to assigns the individual label value to each region. In this paper an improved equivalent table algorithm to be simpler and faster than the previous tangled complex labelling algorithm will be proposed when grouping different labels to the same region. 8 steps algorithms for grouping in the equivalent table will be presented and the yielding results will be shown.

A Comparison of Superpixel Characteristics based on SLIC(Simple Linear Iterative Clustering) for Color Feature Spaces (칼라특징공간별 SLIC기반 슈퍼픽셀의 특성비교)

  • Lee, Jeong Hwan
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.10 no.4
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    • pp.151-160
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    • 2014
  • In this paper, a comparison of superpixel characteristics based on SLIC(simple linear iterative clustering) for several color feature spaces is presented. Computer vision applications have come to rely increasingly on superpixels in recent years. Superpixel algorithms group pixels into perceptually meaningful atomic regions, which can be used to replace the rigid structure of the pixel grid. A superpixel is consist of pixels with similar features such as luminance, color, textures etc. Thus superpixels are more efficient than pixels in case of large scale image processing. Generally superpixel characteristics are described by uniformity, boundary precision and recall, compactness. However previous methods only generate superpixels a special color space but lack researches on superpixel characteristics. Therefore we present superpixel characteristics based on SLIC as known popular. In this paper, Lab, Luv, LCH, HSV, YIQ and RGB color feature spaces are used. Uniformity, compactness, boundary precision and recall are measured for comparing characteristics of superpixel. For computer simulation, Berkeley image database(BSD300) is used and Lab color space is superior to the others by the experimental results.

Development of an Automatic 3D Coregistration Technique of Brain PET and MR Images (뇌 PET과 MR 영상의 자동화된 3차원적 합성기법 개발)

  • Lee, Jae-Sung;Kwark, Cheol-Eun;Lee, Dong-Soo;Chung, June-Key;Lee, Myung-Chul;Park, Kwang-Suk
    • The Korean Journal of Nuclear Medicine
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    • v.32 no.5
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    • pp.414-424
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    • 1998
  • Purpose: Cross-modality coregistration of positron emission tomography (PET) and magnetic resonance imaging (MR) could enhance the clinical information. In this study we propose a refined technique to improve the robustness of registration, and to implement more realistic visualization of the coregistered images. Materials and Methods: Using the sinogram of PET emission scan, we extracted the robust head boundary and used boundary-enhanced PET to coregister PET with MR. The pixels having 10% of maximum pixel value were considered as the boundary of sinogram. Boundary pixel values were exchanged with maximum value of sinogram. One hundred eighty boundary points were extracted at intervals of about 2 degree using simple threshold method from each slice of MR images. Best affined transformation between the two point sets was performed using least square fitting which should minimize the sum of Euclidean distance between the point sets. We reduced calculation time using pre-defined distance map. Finally we developed an automatic coregistration program using this boundary detection and surface matching technique. We designed a new weighted normalization technique to display the coregistered PET and MR images simultaneously. Results: Using our newly developed method, robust extraction of head boundary was possible and spatial registration was successfully performed. Mean displacement error was less than 2.0 mm. In visualization of coregistered images using weighted normalization method, structures shown in MR image could be realistically represented. Conclusion: Our refined technique could practically enhance the performance of automated three dimensional coregistration.

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