• Title/Summary/Keyword: A Multi-region

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Detection of Pavement Region with Structural Patterns through Adaptive Multi-Seed Region Growing (적응적 다중 시드 영역 확장법을 이용한 구조적 패턴의 보도 영역 검출)

  • Weon, Sun-Hee;Joo, Sung-Il;Na, Hyeon-Suk;Choi, Hyung-Il
    • The KIPS Transactions:PartB
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    • v.19B no.4
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    • pp.209-220
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    • 2012
  • In this paper, we propose an adaptive pavement region detection method that is robust to changes of structural patterns in a natural scene. In order to segment out a pavement reliably, we propose two step approaches. We first detect the borderline of a pavement and separate out the candidate region of a pavement using VRays. The VRays are straight lines starting from a vanishing point. They split out the candidate region that includes the pavement in a radial shape. Once the candidate region is found, we next employ the adaptive multi-seed region growing(A-MSRG) method within the candidate region. The A-MSRG method segments out the pavement region very accurately by growing seed regions. The number of seed regions are to be determined adaptively depending on the encountered situation. We prove the effectiveness of our approach by comparing its performance against the performances of seed region growing(SRG) approach and multi-seed region growing(MSRG) approach in terms of the false detection rate.

Region-based Multi-level Thresholding for Color Image Segmentation (영역 기반의 Multi-level Thresholding에 의한 컬러 영상 분할)

  • Oh, Jun-Taek;Kim, Wook-Hyun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.6 s.312
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    • pp.20-27
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    • 2006
  • Multi-level thresholding is a method that is widely used in image segmentation. However most of the existing methods are not suited to be directly used in applicable fields and moreover expanded until a step of image segmentation. This paper proposes region-based multi-level thresholding as an image segmentation method. At first we classify pixels of each color channel to two clusters by using EWFCM(Entropy-based Weighted Fuzzy C-Means) algorithm that is an improved FCM algorithm with spatial information between pixels. To obtain better segmentation results, a reduction of clusters is then performed by a region-based reclassification step based on a similarity between regions existing in a cluster and the other clusters. The clusters are created using the classification information of pixels according to color channel. We finally perform a region merging by Bayesian algorithm based on Kullback-Leibler distance between a region and the neighboring regions as a post-processing method as many regions still exist in image. Experiments show that region-based multi-level thresholding is superior to cluster-, pixel-based multi-level thresholding, and the existing mettled. And much better segmentation results are obtained by the post-processing method.

Multi-Dimensional Vector Approximation Tree with Dynamic Bit Allocation (동적 비트 할당을 통한 다차원 벡터 근사 트리)

  • 복경수;허정필;유재수
    • The Journal of the Korea Contents Association
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    • v.4 no.3
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    • pp.81-90
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    • 2004
  • Recently, It has been increased to use a multi-dimensional data in various applications with a rapid growth of the computing environment. In this paper, we propose the vector approximate tree for content-based retrieval of multi-dimensional data. The proposed index structure reduces the depth of tree by storing the many region information in a node because of representing region information using space partition based method and vector approximation method. Also it efficiently handles 'dimensionality curse' that causes a problem of multi-dimensional index structure by assigning the multi-dimensional data space to dynamic bit. And it provides the more correct regions by representing the child region information as the parent region information relatively. We show that our index structure outperforms the existing index structure by various experimental evaluations.

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The study on efficient transport system in Circle Yellow-Sea region using rail & sea multi transport system (철도-해운 복합운송 시스템을 이용한 환황해권 수송 효율화 연구)

  • Han, Ji-Young;Yoo, Jae-Kyun;Lee, Yoon-Mi
    • Proceedings of the KSR Conference
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    • 2010.06a
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    • pp.389-396
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    • 2010
  • After analyzing network of the region of western sea, which is the center of Circle Yellow-Sea economic region, and Circle Bo-Hai and the delta of a long river economic region, which are belong to three major economic region of China, as an efficient strategy, rail & sea multi-transport system of Korea-China joint SOC strategy is suggested. Rail & Sea multi-transport system, which is the links of railroads and shipping transport, can be subdivided into train-ferry, which is the transport of loaded trains into a vessel, and transshipment, which is transshipment of containers from railroads to vessels. And, the way of railroads transport through a tunnel under the sea is also suggested.

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Multi-views face detection in Omni-directional camera for non-intrusive iris recognition (비강압적 홍채 인식을 위한 전 방향 카메라에서의 다각도 얼굴 검출)

  • 이현수;배광혁;김재희;박강령
    • Proceedings of the IEEK Conference
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    • 2003.11b
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    • pp.115-118
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    • 2003
  • This paper describes a system of detecting multi-views faces and estimating their face poses in an omni-directional camera environment for non-intrusive iris recognition. The paper is divided into two parts; First, moving region is identified by using difference-image information. Then this region is analyzed with face-color information to find the face candidate region. Second part is applying PCA (Principal Component Analysis) to detect multi-view faces, to estimate face pose.

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Multi-level Thresholding using Fuzzy Clustering Algorithm in Local Entropy-based Transition Region (지역적 엔트로피 기반 전이 영역에서 퍼지 클러스터링 알고리즘을 이용한 Multi-Level Thresholding)

  • Oh, Jun-Taek;Kim, Bo-Ram;Kim, Wook-Hyun
    • The KIPS Transactions:PartB
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    • v.12B no.5 s.101
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    • pp.587-594
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    • 2005
  • This paper proposes a multi-level thresholding method for image segmentation using fuzzy clustering algorithm in transition region. Most of threshold-based image segmentation methods determine thresholds based on the histogram distribution of a given image. Therefore, the methods have difficulty in determining thresholds for real-image, which has a complex and undistinguished distribution, and demand much computational time and memory size. To solve these problems, we determine thresholds for real-image using fuzzy clustering algorithm after extracting transition region consisting of essential and important components in image. Transition region is extracted based on Inか entropy, which is robust to noise and is well-known as a tool that describes image information. And fuzzy clustering algorithm can determine optimal thresholds for real-image and be easily extended to multi-level thresholding. The experimental results demonstrate the effectiveness of the proposed method for performance.

Multi-Region Structural-Acoustic Coupling Analysis on Noise Reduction of Layered Structures using Finite Element and Boundary Element Technique (경계요소법과 유한요소법에 의한 흡음판의 소음저감에 관한 다영역 연성해석)

  • Ju, Hyun-Don;Seo, Won-Jin;Lee, Shi-Bok
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2000.06a
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    • pp.309-313
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    • 2000
  • A structural-acoustic coupling problem involving fluid in a cavity divided with flexible walls and porous materials is investigated in this paper. In many practical problems, the use of finite elements to discretize the fluid region leads to large stiffness and mass matrices. But, since the acoustic boundary element discretization requires to put elements only on the surface of structure, the size of matrices is reduced considerably. Here, we developed a numerical analysis program for the structural-acoustic coupling problems of the multi-region cavity, using boundary elements for the fluid regions and finite elements for the structure. By considering sound transmission through layered systems placed in a cavity, the accuracy of the coupled acoustical-structural finite element model has been verified by comparing its transmission loss predictions with analytical sloutions. Example problems are included to investigate the characteristics of the multi-region structural-acoustic coupling system with porous material.

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Improved Watershed Image Segmentation Using the Morphological Multi-Scale Gradient

  • Gelegdorj, Jugdergarav;Chu, Hyung-Suk;An, Chong-Koo
    • Journal of the Institute of Convergence Signal Processing
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    • v.12 no.2
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    • pp.91-95
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    • 2011
  • In this paper, we present an improved multi-scale gradient algorithm. The proposed algorithm works the effectively handling of both step and blurred edges. In the proposed algorithm, the image sharpening operator is sharpening the edges and contours of the objects. This operation gives an opportunity to get noise reduced image and step edged image. After that, multi-scale gradient operator works on noise reduced image in order to get a gradient image. The gradient image is segmented by watershed transform. The approach of region merging is used after watershed transform. The region merging is carried out according to the region area and region homogeneity. The region number of the proposed algorithm is 36% shorter than that of the existing algorithm because the proposed algorithm produces a few irrelevant regions. Moreover, the computational time of the proposed algorithm is relatively fast in comparison with the existing one.

Research on the Multi-Focus Image Fusion Method Based on the Lifting Stationary Wavelet Transform

  • Hu, Kaiqun;Feng, Xin
    • Journal of Information Processing Systems
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    • v.14 no.5
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    • pp.1293-1300
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    • 2018
  • For the disadvantages of multi-scale geometric analysis methods such as loss of definition and complex selection of rules in image fusion, an improved multi-focus image fusion method is proposed. First, the initial fused image is quickly obtained based on the lifting stationary wavelet transform, and a simple normalized cut is performed on the initial fused image to obtain different segmented regions. Then, the original image is subjected to NSCT transformation and the absolute value of the high frequency component coefficient in each segmented region is calculated. At last, the region with the largest absolute value is selected as the postfusion region, and the fused multi-focus image is obtained by traversing each segment region. Numerical experiments show that the proposed algorithm can not only simplify the selection of fusion rules, but also overcome loss of definition and has validity.

Piecewise Image Denoising with Multi-scale Block Region Detector based on Quadtree Structure (쿼드트리 기반의 다중 스케일 블록 영역 검출기를 통한 구간적 영상 잡음 제거 기법)

  • Lee, Jeehyun;Jeong, Jechang
    • Journal of Broadcast Engineering
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    • v.20 no.4
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    • pp.521-532
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    • 2015
  • This paper presents a piecewise image denoising with multi-scale block region detector based on quadtree structure for effective image restoration. Proposed piecewise image denoising method suggests multi-scale block region detector (MBRD) by dividing whole pixels of a noisy image into three parts, with regional characteristics: strong variation region, weak variation region, and flat region. These regions are classified according to total pixels variation between multi-scale blocks and are applied principal component analysis with local pixel grouping, bilateral filtering, and structure-preserving image decomposition operator called relative total variation. The performance of proposed method is evaluated by Experimental results. we can observe that region detection results generated by the detector seems to be well classified along the characteristics of regions. In addition, the piecewise image denoising provides the positive gain with regard to PSNR performance. In the visual evaluation, details and edges are preserved efficiently over the each region; therefore, the proposed method effectively reduces the noise and it proves that it improves the performance of denoising by the restoration process according to the region characteristics.