• Title/Summary/Keyword: First detection

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Edge Detection using Windows with Adaptive Threshold (적응형 한계치를 갖는 윈도우를 이용한 에지 검출)

  • 송의석;오하랑;김준형
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.11
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    • pp.1424-1433
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    • 1995
  • The edge detection process serves to simplify the analysis of images by drastically reducing the amount of data to be processed, while preserving useful structural informations about object boundaries. At first, this paper proposes an edge detection algorithm to reduce the amount of computation. The gradients of pixels are calculated by using first order differential equations on the pixels with even rows and even columns or odd rows and odd columns, and they are compared with a threshold to decide edges. As a result, the computational complexity is reduced to one third or one forth compared with the provious ones. To enhance the accuracy of edge detection, a method with the adaptive threshold for each pixel window which is calculated by using characteristic values is proposed. In this case, the performance can be improved since the threshold is calculated properly for each window according to the local characteristics of corresponding window.

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A two-stage structural damage detection method using dynamic responses based on Kalman filter and particle swarm optimization

  • Beygzadeh, Sahar;Torkzadeh, Peyman;Salajegheh, Eysa
    • Structural Engineering and Mechanics
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    • v.83 no.5
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    • pp.593-607
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    • 2022
  • To solve the problem of detecting structural damage, a two-stage method using the Kalman filter and Particle Swarm Optimization (PSO) is proposed. In this method, the first PSO population is enhanced using the Kalman filter method based on dynamic responses. Due to noise in the sensor responses and errors in the damage detection process, the accuracy of the damage detection process is reduced. This method proposes a novel approach for solve this problem by integrating the Kalman filter and sensitivity analysis. In the Kalman filter, an approximate damage equation is considered as the equation of state and the damage detection equation based on sensitivity analysis is considered as the observation equation. The first population of PSO are the random damage scenarios. These damage scenarios are estimated using a step of the Kalman filter. The results of this stage are then used to detect the exact location of the damage and its severity with the PSO algorithm. The efficiency of the proposed method is investigated using three numerical examples: a 31-element planer truss, a 52-element space dome, and a 56-element space truss. In these examples, damage is detected for several scenarios in two states: using the no noise responses and using the noisy responses. The results show that the precision and efficiency of the proposed method are appropriate in structural damage detection.

Face Detection using PCA-LDA and Color Information (색상정보와 PCA-LDA를 이용한 얼굴검출)

  • Lee, Ju-Seung;Han, Young-Hwan;Hong, Seung-Hong
    • Journal of IKEEE
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    • v.6 no.1 s.10
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    • pp.72-79
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    • 2002
  • This paper presents an efficient face detection algorithm for color images with a complex background. The presented algorithm utilizes the color information and eigenface that is calculated by PCA-LDA (Principle Component Analysis - Linear Discriminant Analysis). The method of using the color information is faster than any other methods. Eigenface includes average information of the whole test faces. Therefore eigenface can decide that the candidate region is a face. The whole process is composed of two steps. First, it finds first face candidates region of skin tone using a color information in image. We can get a size and position of face candidate region. Second, we compare first face candidate region with eigenface, so decide that an image whether include a face or not. The advantages of the proposed approach include that increasing the detection speed by deciding a size and position of first face candidates region. Also, Betting 97% of the detection rate by comparing the eigenfaces calculated in PCA-LDA.

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A Study on Real-time Face Detection in Video (동영상에서 실시간 얼굴검출에 관한 연구)

  • Kim, Hyeong-Gyun;Bae, Yong-Guen
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.2
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    • pp.47-53
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    • 2010
  • This paper proposed Residual Image detection and Color Info using the face detection technique. The proposed technique was fast processing speed and high rate of face detection on the video. In addition, this technique is to detection error rate reduced through the calibration tasks for tilted face image. The first process is to extract target image from the transmitted video images. Next, extracted image processed by window rotated algorithm for detection of tilted face image. Feature extraction for face detection was used for AdaBoost algorithm.

Microarrays for the Detection of HBV and HDV

  • Sun, Zhaohui;Zheng, Wenling;Zhang, Bao;Shi, Rong;Ma, Wenli
    • BMB Reports
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    • v.37 no.5
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    • pp.546-551
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    • 2004
  • The increasing pace of development in molecular biology during the last decade has had a direct effect on mass testing and diagnostic applications, including blood screening. We report the model Microarray that has been developed for Hepatitis B virus (HBV) and Hepatitis D virus (HDV) detection. The specific primer pairs of PCR were designed using the Primer Premier 5.00 program according to the conserved regions of HBV and HDV. PCR fragments were purified and cloned into pMD18-T vectors. The recombinant plasmids were extracted from positive clones and the target gene fragments were sequenced. The DNA microarray was prepared by robotically spotting PCR products onto the surface of glass slides. Sequences were aligned, and the results obtained showed that the products of PCR amplification were the required specific gene fragments of HBV, and HDV. Samples were labeled by Restriction Display PCR (RD-PCR). Gene chip hybridizing signals showed that the specificity and sensitivity required for HBV and HDV detection were satisfied. Using PCR amplified products to construct gene chips for the simultaneous clinical diagnosis of HBV and HDV resulted in a quick, simple, and effective method. We conclude that the DNA microarray assay system might be useful as a diagnostic technique in the clinical laboratory. Further applications of RD-PCR for the sample labeling could speed up microarray multi-virus detection.

A Simple Enhancement of Coherent Detection for Initial Frame Synchronization in W-CDMA Systems (W-CDMA 시스템의 초기 프레임 동기 획득을 위한 Coherent 검출 방식의 성능 개선)

  • Choi, Won-Eung;Joo, Jung-Suk
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.47 no.10
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    • pp.43-48
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    • 2010
  • In general, in order to reduce an initial cell searching time, W-CDMA systems adopt a three-step cell search scheme: slot synchronization, frame synchronization, and primary scrambling code identification. We consider the second step (frame synchronization), in which a coherent detection using P-SCH (primary synchronization channel) is possible. In this paper, we propose a new coherent detection scheme, where a first order recursive filter is used to enhance channel estimation performance. Computer simulation results indicate that the detection performance of the proposed scheme can be robust over large range of frequency offset.

A Study on Design Parameters for Ready-made Ear Shell of Hearing Aids (보청기용 범용 이어쉘을 위한 설계 파라미터에 관한 연구)

  • Urtnasan, Erdenebayar;Jeon, Yu-Yong;Park, Gyu-Seok;Song, Young-Rok;Lee, Sang-Min
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.5
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    • pp.1055-1061
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    • 2011
  • In this study, main parameters: aperture, first bend and second bend which express a structure of ear canal are extracted in order to modeling and manufacture the ready-made ear shells of hearing aids. The proposed parameter extraction method consists of 2 important algorithms, aperture detection and feature detection. In the aperture detection algorithm, aperture of 3-D scanned virtual ear impression and parameters relating to ear shell of hearing aid are determined. The feature detection algorithm detects first bend, second bend, and related parameters. Through these two algorithms, parameters for aperture, first bend, and second bend are extracted to model the ready-made ear shell of hearing aid. The values of these extracted parameters from 36 people's right ear impression are analyzed and measured statistically. As a result of the analysis, it has been found that it is possible to classify ready-made ear shell parameters by age and size. The ready-made ear shell parameters are classified 3-size for 20 years old and 2-size for 60 years olde. Using 3D rhino program, virtual ready-made ear shell is reconstructed by parameters of every type, and simulated to model it. A final product was produced by transferring simulation result with rapid prototyping system. The modeled ready-made ear shell is evaluated with the objective and subjective method. Objective method is the comparison volume ratio and overlapped volume ratio of ear impression from randomly chosen 18 people and ready-made ear shell. And subjective method is that the final product of ready-made ear shell is used by users and the satisfaction number drawn from well fitting and comfortable testing was evaluated. In the result of the evaluation, it has been found that volume ration is 70%, big and middle size ready-made ear shell products are possible, and the satisfaction number is high.

Analyses of Design for Intrusion Detection System based on Hardware Architecture (하드웨어 기반의 침입탑지 시스템의 설계에 대한 분석)

  • Kim, Jung-Tae
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.05a
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    • pp.666-669
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    • 2008
  • A number of intrusion detection systems have been developed to detect intrusive activity on individual hosts and networks. The systems developed rely almost exclusively on a software approach to intrusion detection analysis and response. In addition, the network systems developed apply a centralized approach to the detection of intrusive activity. The problems introduced by this approach are twofold. First the centralization of these functions becomes untenable as the size of the network increases.

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Flame Dection Algorithm with Motion Vector (모션 벡터를 이용한 화염 검출 알고리즘)

  • Park, Jang-Sik;Bae, Jong-Gab;Choi, Soo-Young
    • Proceedings of the Korea Institute of Fire Science and Engineering Conference
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    • 2008.04a
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    • pp.135-138
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    • 2008
  • Many Victims and property damage are caused in fires. In this paper, an flame detection algorithm is proposed to early alarm fires. The proposed flame detection algorithm is based on 2-stage decision strategy of video processing. The first decision is to check with color distribution of input vidoe. In the second, the candidated region is settled as fire region with activity. As a result of simulation, it is shown that the proposed algorithm is useful for fire recognition.

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Model updating and damage detection in multi-story shear frames using Salp Swarm Algorithm

  • Ghannadi, Parsa;Kourehli, Seyed Sina
    • Earthquakes and Structures
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    • v.17 no.1
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    • pp.63-73
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    • 2019
  • This paper studies damage detection as an optimization problem. A new objective function based on changes in natural frequencies, and Natural Frequency Vector Assurance Criterion (NFVAC) was developed. Due to their easy and fast acquisition, natural frequencies were utilized to detect structural damages. Moreover, they are sensitive to stiffness reduction. The method presented here consists of two stages. Firstly, Finite Element Model (FEM) is updated. Secondly, damage severities and locations are determined. To minimize the proposed objective function, a new bio-inspired optimization algorithm called salp swarm was employed. Efficiency of the method presented here is validated by three experimental examples. The first example relates to three-story shear frame with two single damage cases in the first story. The second relates to a five-story shear frame with single and multiple damage cases in the first and third stories. The last one relates to a large-scale eight-story shear frame with minor damage case in the first and third stories. Moreover, the performance of Salp Swarm Algorithm (SSA) was compared with Particle Swarm Optimization (PSO). The results show that better accuracy is obtained using SSA than using PSO. The obtained results clearly indicate that the proposed method can be used to determine accurately and efficiently both damage location and severity in multi-story shear frames.