• Title/Summary/Keyword: Multi-Region

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IMBE Model Based SNR Estimation of Continuous Speech Signals (연속음성신호에서 IMBE 모델을 이용한 SNR 추정 연구)

  • Park, Hyung-Woo;Bae, Myung-Jin
    • The Journal of the Acoustical Society of Korea
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    • v.29 no.2
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    • pp.148-153
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    • 2010
  • In speech signal processing, speech signal corrupted by noise should be enhanced to improve quality. Usually noise estimation methods need flexibility for variable environment. Noise profile is renewed on silence region to avoid effects of speech properties. So we have to preprocess finding voice region before noise estimation. However, if received signal does not have silence region, we cannot apply that method. In this paper, we proposed SNR estimation method for continuous speech signal. A Speech signal consists of Voice and Unvoiced Band in The MBE excitation model. And the energy of speech signal is mostly distributed on voiced region, so we can estimate SNR by the ratio of voiced region energy to unvoiced. We use the IMBE vocoder for the Voice or Unvoice band of segmented speech signal. Continuously we calculate the segmented SNR using that information and the energy of each band. And we estimate the SNR of continuous speech signal.

A Comparative Study of Algorithms for Multi-Aspect Target Classifications (다중 각도 정보를 이용한 표적 구분 알고리즘 비교에 관한 연구)

  • 정호령;김경태;김효태
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.15 no.6
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    • pp.579-589
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    • 2004
  • The radar signals are generally very sensitive to relative orientations between radar and target. Thus, the performance of a target recognition system significantly deteriorates as the region of aspect angles becomes broader. To address this difficulty, in this paper, we propose a method based on the multi-aspect information in order to improve the classification capability ever for a wide angular region. First, range profiles are used to extract feature vectors based on the central moments and principal component analysis(PCA). Then, a classifier with the use of multi-aspect information is applied to them, yielding an additional improvement of target recognition capability. There are two different strategies among the classifiers that can fuse the information from multi-aspect radar signals: independent methodology and dependent methodology. In this study, the performances of the two strategies are compared within the frame work of target recognition. The radar cross section(RCS) data of six aircraft models measured at compact range of Pohang University of Science and Technology are used to demonstrate and compare the performances of the two strategies.

Damage detection on a full-scale highway sign structure with a distributed wireless sensor network

  • Sun, Zhuoxiong;Krishnan, Sriram;Hackmann, Greg;Yan, Guirong;Dyke, Shirley J.;Lu, Chenyang;Irfanoglu, Ayhan
    • Smart Structures and Systems
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    • v.16 no.1
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    • pp.223-242
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    • 2015
  • Wireless sensor networks (WSNs) have emerged as a novel solution to many of the challenges of structural health monitoring (SHM) in civil engineering structures. While research projects using WSNs are ongoing worldwide, implementations of WSNs on full-scale structures are limited. In this study, a WSN is deployed on a full-scale 17.3m-long, 11-bay highway sign support structure to investigate the ability to use vibration response data to detect damage induced in the structure. A multi-level damage detection strategy is employed for this structure: the Angle-between-String-and-Horizon (ASH) flexibility-based algorithm as the Level I and the Axial Strain (AS) flexibility-based algorithm as the Level II. For the proposed multi-level damage detection strategy, a coarse resolution Level I damage detection will be conducted first to detect the damaged region(s). Subsequently, a fine resolution Level II damage detection will be conducted in the damaged region(s) to locate the damaged element(s). Several damage cases are created on the full-scale highway sign support structure to validate the multi-level detection strategy. The multi-level damage detection strategy is shown to be successful in detecting damage in the structure in these cases.

A Study on the Fabrication of Heater based on Silicone Rubber (실리콘러버 기반의 히터제작에 관한 연구)

  • Jeong-Oh Hong;Jae Tack Hong;Shin-Hyeong Choi
    • Advanced Industrial SCIence
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    • v.2 no.2
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    • pp.9-15
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    • 2023
  • Since silicone rubber heaters are flexible, they can be directly attached or installed in objects to be heated even in flat, curved or three-dimensional shapes. Since the current heating method heats the entire object to be heated and raises it to a required temperature, ignoring areas or positions where heat is not required, partial intensive heating cannot be performed. When using multi-heating zones, rather than heating the entire object to be heated, only the parts that need heat are intensively heated according to the process, so it is possible to heat quickly by local location by applying different amounts of heat with a small amount of electric capacity to each place that needs heat, and heat energy can reduce. In this study, the temperature and heating time of the partially concentrated region in the multi-heating region structure are measured so that a uniform temperature or temperature difference occurs in the region requiring thermal fusion. In order to determine the optimal power density range and reduce capacitance, the safety of a silicon rubber heater manufactured with a multi-heating zone structure is investigated. If the silicon rubber heater is manufactured in a multi-heating method, the multi-intensive heating technology can be ideally applied to all heating processes.

A New Mapping Algorithm for Depth Perception in 3D Screen and Its Implementation (3차원 영상의 깊이 인식에 대한 매핑 알고리즘 구현)

  • Ham, Woon-Chul;Kim, Seung-Hwan
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.45 no.6
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    • pp.95-101
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    • 2008
  • In this paper, we present a new smoothing algorithm for variable depth mapping for real time stereoscopic image for 3D display. Proposed algorithm is based on the physical concept, called Laplacian equation and we also discuss the mapping of the depth from scene to displayed image. The approach to solve the problem in stereoscopic image which we adopt in this paper is similar to multi-region algorithm which was proposed by N.Holliman. The main difference thing in our algorithm compared with the N.Holliman's multi-region algorithm is that we use the Laplacian equation by considering the distance between viewer and object. We implement the real time stereoscopic image generation method for OpenGL on the circular polarized LCD screen to demonstrate its real functioning in the visual sensory system in human brain. Even though we make and use artificial objects by using OpenGL to simulate the proposed algorithm we assure that this technology may be applied to stereoscopic camera system not only for personal computer system but also for public broad cast system.

Infrared Image Segmentation by Extracting and Merging Region of Interest (관심영역 추출과 통합에 의한 적외선 영상 분할)

  • Yeom, Seokwon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.26 no.6
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    • pp.493-497
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    • 2016
  • Infrared (IR) imaging is capable of detecting targets that are not visible at night, thus it has been widely used for the security and defense system. However, the quality of the IR image is often degraded by low resolution and noise corruption. This paper addresses target segmentation with the IR image. Multiple regions of interest (ROI) are extracted by the multi-level segmentation and targets are segmented from the individual ROI. Each level of the multi-level segmentation is composed of a k-means clustering algorithm an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering algorithm initializes the parameters of the Gaussian mixture model (GMM) and the EM algorithm iteratively estimates those parameters. Each pixel is assigned to one of clusters during the decision. This paper proposes the selection and the merging of the extracted ROIs. ROI regions are selectively merged in order to include the overlapped ROI windows. In the experiments, the proposed method is tested on an IR image capturing two pedestrians at night. The performance is compared with conventional methods showing that the proposed method outperforms others.

RAG-based Image Segmentation Using Multiple Windows (RAG 기반 다중 창 영상 분할 (1))

  • Lee, Sang-Hoon
    • Korean Journal of Remote Sensing
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    • v.22 no.6
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    • pp.601-612
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    • 2006
  • This study proposes RAG (Region Adjancency Graph)-based image segmentation for large imagery in remote sensing. The proposed algorithm uses CN-chain linking for computational efficiency and multi-window operation of sliding structure for memory efficiency. Region-merging due to RAG is a process to find an edge of the best merge and update the graph according to the merge. The CN-chain linking constructs a chain of the closest neighbors and finds the edge for merging two adjacent regions. It makes the computation time increase as much as an exact multiple in the increasement of image size. An RNV (Regional Neighbor Vector) is used to update the RAG according to the change in image configuration due to merging at each step. The analysis of large images requires an enormous amount of computational memory. The proposed sliding multi-window operation with horizontal structure considerably the memory capacity required for the analysis and then make it possible to apply the RAG-based segmentation for very large images. In this study, the proposed algorithm has been extensively evaluated using simulated images and the results have shown its potentiality for the application of remotely-sensed imagery.

Multi-Region based Radial GCN algorithm for Human action Recognition (행동인식을 위한 다중 영역 기반 방사형 GCN 알고리즘)

  • Jang, Han Byul;Lee, Chil Woo
    • Smart Media Journal
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    • v.11 no.1
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    • pp.46-57
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    • 2022
  • In this paper, multi-region based Radial Graph Convolutional Network (MRGCN) algorithm which can perform end-to-end action recognition using the optical flow and gradient of input image is described. Because this method does not use information of skeleton that is difficult to acquire and complicated to estimate, it can be used in general CCTV environment in which only video camera is used. The novelty of MRGCN is that it expresses the optical flow and gradient of the input image as directional histograms and then converts it into six feature vectors to reduce the amount of computational load and uses a newly developed radial type network model to hierarchically propagate the deformation and shape change of the human body in spatio-temporal space. Another important feature is that the data input areas are arranged being overlapped each other, so that information is not spatially disconnected among input nodes. As a result of performing MRGCN's action recognition performance evaluation experiment for 30 actions, it was possible to obtain Top-1 accuracy of 84.78%, which is superior to the existing GCN-based action recognition method using skeleton data as an input.

An Algorithm for Inspection System of Can Print-Errors (캔 인쇄 불량 검사 시스템을 위한 알고리즘)

  • 이현민;김만진;이칠우
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2275-2278
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    • 2003
  • In this paper, we propose a visual inspection algorithm to detect can print-errors by using multi-camera and image valuing algorithm. The features of the algorithm are to use four cameras that are arranged with 90$^{\circ}$ between each other and to adopt a synthesized image model which represents whole surface of a can. Using the model, detection process is straight forward, namely it is comparing a partial region of the can to a specific region of the model where is previously marked.

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MQW electroabsorption modulator integrated with a tapered waveguide vertical interconnect

  • Han, Sang-Kook
    • Journal of the Optical Society of Korea
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    • v.1 no.1
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    • pp.44-47
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    • 1997
  • The integration of a GaAs/AlGaAs multi-quantum well electroabsorption modulator and a tapered waveguide vertical direction optical interconnect has been performed without the complicated regrowth process. Zn impurity-induced layer disordering of MQW layer is used to achieve the energy transfer between SQW and MQW regions. Light coupled into a SQW region was transferred to an MQW region and an intensity modulation of 10 dB extinction ratio was demonstrated.