• Title/Summary/Keyword: number plate detection

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FPGA based System for Pinhole Detection in Cold Rolled Steel (FPGA 기반의 냉연강판 핀홀 검출 시스템)

  • Ha, Sung-Kil;Lee, Jung Eun;Moon, Woo Sung;Baek, Kwang Ryul
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.8
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    • pp.742-747
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    • 2015
  • The quality of steel plate products is determined by the number of defects and the process problems are estimated by shapes of defects. Therefore pinholes defects of cold rolled steel have to be controlled. In order to improve productivity and quality of products, within each production process, the product is inspected by an adequate inspection system individually in the lines of steelworks. Among a number of inspection systems, we focus on the pinholes detection system. In this paper, we propose an embedded system using FPGA which can detect pinholes defects. The proposed system is smaller and more flexible than a traditional system based on expensive frame grabbers and PC. In order to detect consecutive defects, FPGAs acquire two dimensional image and process the image in real time by using correlation of lines. The proposed pinholes detection algorithm decreases arithmetic operations of image processing and also we designed the hardware to shorten the data path between logics due to decreasing propagation delay. The experimental results show that the proposed embedded system detects the reliable number of pinholes in real time.

Experiment on Collection Characteristics of Sub micron Particles in Two-Stage Parallel-Plate Electrostatic Precipitators (2단 평행판 전기집진기의 서브마이크론 입자 포집특성 실험)

  • Oh, M.D.;Yoo, K.H.
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.6 no.3
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    • pp.237-246
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    • 1994
  • Experimental data are reported for charging and collection of NaCl aerosols in the 0.03- to $0.2{\mu}m$-geometric-mean-diameter range in 2-stage parallel-plate electrostatic precipitators. The NaCl aerosols are generated with geometric standard deviation of about 1.74 and particle generation rate of about 10^9 particles/see by the constant output atomizer and injected into the air flow in the clean wind-tunnel. The 2-stage parallel-plate electrostatic precipitator installed in the test section of the wind-tunnel is operated with a positive corona discharge. The NaCl aerosols in the channel flow are sampled and transported to the aerosol particle number concentration measurement system by using the isoaxial sampling and transport system constructed based on the Okazaki and Willeke design. The aerosol particle number concentration measurement system measures the size distribution of submicrometer aerosols by an electrical mobility detection technique. It is confirmed from comparing the measured collection efficiencies in this study and the predicted ones by our previous theoretical analysis that the predicted collection efficiencies agree well with the experimental ones. It is also found from the comparison that below about $0.02{\mu}m$ all particles are not charged and the uncharged particles are not collected, and consequently 2-stage parallel-plate electrostatic precipitators are not suitable for that particle size range.

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A K-Ray Image Reconstruction by the Direct Detection Method (직접검출방식(直接檢出方式)에 의한 X선영상(X線影像)의 재구성(再構成)에 관(關)한 연구(硏究))

  • Kang, Hee-Doo
    • Journal of radiological science and technology
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    • v.14 no.1
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    • pp.61-72
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    • 1991
  • In this paper, the rotating plate method extracting signal and reconstructing original image was proposed. The rotating methode has cell detector array each of which has used in the medical diagnosis X-ray photography. The major problem using the simple horizontal moving or non-moving methode is the size and number of detector cells which have the considerable affection on the sharpness and resolution of the reconstructed image. Secondary, the estimated pixel values of non-detected real points which are placed between detector cells will be the distorted pixels in the reconstructed image. Therefore, the proposed rotating plate method has the exact distribution on the uncertain pixels which were reconstructed by conventional methods to solve there problems. And then, the image using the rotated plate's cell out put signal was reconstructed on the computer simulation. The method will rotated the detector array plate to solve the reconstruction from the detector size and number of conventional methods. The result of simulation has estimated the original pixel position and 81 pixel/mm resolution which the reconsiderlation of the detector's moving orientation, the proposed method has 25 pixel/mm resolution. These results have been represented by 3-D computer graphics.

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Detection of a Crack on a Plate by IDT Type Lamb Wave Sensors (IDT형 Lamb 파 센서에 의한 판상의 균열 검출)

  • Kim, Jun-Ho;Roh, Yong-Rae
    • The Journal of the Acoustical Society of Korea
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    • v.29 no.8
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    • pp.483-490
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    • 2010
  • In this paper, an Inter-Digital Transducer (IDT) type Lamb wave sensor is proposed to estimate the geometry and number of cracks on a plate structure, and its validity is checked through experiments. This IDT type sensor is more readily controllable than conventional patch type piezoelectric sensors to modify its operation frequency and directionality by altering its finger patterns. In this work, omni-directional annular IDT and highly directional rectangular IDT sensors are designed and fabricated. The IDT sensors are used to diagnose the length, number and orientation of cracks on an aluminum plate by measuring the amplitude and time of flight of Lamb waves. The results are analyzed to discuss the efficacy of the IDT sensors.

Real-Time Vehicle License Plate Recognition System Using Adaptive Heuristic Segmentation Algorithm (적응 휴리스틱 분할 알고리즘을 이용한 실시간 차량 번호판 인식 시스템)

  • Jin, Moon Yong;Park, Jong Bin;Lee, Dong Suk;Park, Dong Sun
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.9
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    • pp.361-368
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    • 2014
  • The LPR(License plate recognition) system has been developed to efficient control for complex traffic environment and currently be used in many places. However, because of light, noise, background changes, environmental changes, damaged plate, it only works limited environment, so it is difficult to use in real-time. This paper presents a heuristic segmentation algorithm for robust to noise and illumination changes and introduce a real-time license plate recognition system using it. In first step, We detect the plate utilized Haar-like feature and Adaboost. This method is possible to rapid detection used integral image and cascade structure. Second step, we determine the type of license plate with adaptive histogram equalization, bilateral filtering for denoise and segment accurate character based on adaptive threshold, pixel projection and associated with the prior knowledge. The last step is character recognition that used histogram of oriented gradients (HOG) and multi-layer perceptron(MLP) for number recognition and support vector machine(SVM) for number and Korean character classifier respectively. The experimental results show license plate detection rate of 94.29%, license plate false alarm rate of 2.94%. In character segmentation method, character hit rate is 97.23% and character false alarm rate is 1.37%. And in character recognition, the average character recognition rate is 98.38%. Total average running time in our proposed method is 140ms. It is possible to be real-time system with efficiency and robustness.

Crack detection in folded plates with back-propagated artificial neural network

  • Oguzhan Das;Can Gonenli;Duygu Bagci Das
    • Steel and Composite Structures
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    • v.46 no.3
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    • pp.319-334
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    • 2023
  • Localizing damages is an essential task to monitor the health of the structures since they may not be able to operate anymore. Among the damage detection techniques, non-destructive methods are considerably more preferred than destructive methods since damage can be located without affecting the structural integrity. However, these methods have several drawbacks in terms of detecting abilities, time consumption, cost, and hardware or software requirements. Employing artificial intelligence techniques could overcome such issues and could provide a powerful damage detection model if the technique is utilized correctly. In this study, the crack localization in flat and folded plate structures has been conducted by employing a Backpropagated Artificial Neural Network (BPANN). For this purpose, cracks with 18 different dimensions in thin, flat, and folded structures having 150, 300, 450, and 600 folding angle have been modeled and subjected to free vibration analysis by employing the Classical Plate Theory with Finite Element Method. A Four-nodded quadrilateral element having six degrees of freedom has been considered to represent those structures mathematically. The first ten natural frequencies have been obtained regarding healthy and cracked structures. To localize the crack, the ratios of the frequencies of the cracked flat and folded structures to those of healthy ones have been taken into account. Those ratios have been given to BPANN as the input variables, while the crack locations have been considered as the output variables. A total of 500 crack locations have been regarded within the dataset obtained from the results of the free vibration analysis. To build the best intelligent model, a feature search has been conducted for BAPNN regarding activation function, the number of hidden layers, and the number of hidden neurons. Regarding the analysis results, it is concluded that the BPANN is able to localize the cracks with an average accuracy of 95.12%.

Damage detection in plate structures using frequency response function and 2D-PCA

  • Khoshnoudian, Faramarz;Bokaeian, Vahid
    • Smart Structures and Systems
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    • v.20 no.4
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    • pp.427-440
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    • 2017
  • One of the suitable structural damage detection methods using vibrational characteristics are damage-index-based methods. In this study, a damage index for identifying damages in plate structures using frequency response function (FRF) data has been provided. One of the significant challenges of identifying the damages in plate structures is high number of degrees of freedom resulting in decreased damage identifying accuracy. On the other hand, FRF data are of high volume and this dramatically decreases the computing speed and increases the memory necessary to store the data, which makes the use of this method difficult. In this study, FRF data are compressed using two-dimensional principal component analysis (2D-PCA), and then converted into damage index vectors. The damage indices, each of which represents a specific condition of intact or damaged structures are stored in a database. After computing damage index of structure with unknown damage and using algorithm of lookup tables, the structural damage including the severity and location of the damage will be identified. In this study, damage detection accuracy using the proposed damage index in square-shaped structural plates with dimensions of 3, 7 and 10 meters and with boundary conditions of four simply supported edges (4S), three clamped edges (3C), and four clamped edges (4C) under various single and multiple-element damage scenarios have been studied. Furthermore, in order to model uncertainties of measurement, insensitivity of this method to noises in the data measured by applying values of 5, 10, 15 and 20 percent of normal Gaussian noise to FRF values is discussed.

Some precautions to consider in using wavelet transformation for damage detection analysis of plates

  • Beheshti-Aval, S.B.;Taherinasab, M.;Noori, M.
    • Smart Structures and Systems
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    • v.11 no.1
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    • pp.35-51
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    • 2013
  • Over the last two decades Wavelet Transformation (WT) method has been widely utilized for the damage identification of structures. The main objective of this paper is to discuss and present some of common shortcomings and limitations of mathematical software, as well as other precautionary measures that need to be considered when using them for wavelet analysis applications. Due to popular usage of MATLABMATLAB(R) comparing to other mathematical tools among researchers for data processing of structural responses through WT analysis, this software was chosen for specific study. To the best of the authors' knowledge, these limitations and observations have not been previously identified or discussed in the literature. In this work, a square plate with a severe damage, in form of a crack, parallel to the left edge of the plate is selected for a pilot study. The steady state harmonic response is used for measuring the deflection shape across the line parallel to one edge and perpendicular to the damage. Several criteria and cases such as the smallest size damage that can be detected, correlation between the crack width and the number of sampling points, and the influence of the damage thickness on the accuracy of the result are investigated.

Effect of Cationization Agent Concentration on Glycan Detection Using MALDI TOF-MS

  • Kim, Inyoung;Shin, Dongwon;Paek, Jihyun;Kim, Jeongkwon
    • Mass Spectrometry Letters
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    • v.8 no.1
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    • pp.14-17
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    • 2017
  • The effect of cationization agent concentration on glycan detection via matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was investigated using $Na^+$ ions in the form of NaCl as the cationization agent. NaCl solution concentrations ranging from 1 mM to 1 M were investigated. Glycans from ovalbumin were mixed with the cationization agent solution and the 2,5-dihydroxybenzoic acid (2,5-DHB) matrix solution in a volume ratio of 1:1:1. The resulting mixture was loaded onto the MALDI plate. Two MALDI-TOF MS instruments (Voyager DE-STR MALDI-TOF MS and Tinkerbell RT MALDI-TOF MS) were used for detection of glycans. The best detection, in terms of the number of identified glycans, the peak intensity, and the signal-to-noise (S/N) ratio, was obtained with NaCl concentrations of 0.01-0.1 M for both MALDI-TOF MS instruments.

Image Feature-based Electric Vehicle Detection and Classification System Using Machine Learning (머신 러닝을 이용한 영상 특징 기반 전기차 검출 및 분류 시스템)

  • Kim, Sanghyuk;Kang, Suk-Ju
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.7
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    • pp.1092-1099
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    • 2017
  • This paper proposes a novel way of vehicle detection and classification based on image features. There are two main processes in the proposed system, which are database construction and vehicle classification processes. In the database construction, there is a tight censorship for choosing appropriate images of the training set under the rigorous standard. These images are trained using Haar features for vehicle detection and histogram of oriented gradients extraction for vehicle classification based on the support vector machine. Additionally, in the vehicle detection and classification processes, the region of interest is reset using a number plate to reduce complexity. In the experimental results, the proposed system had the accuracy of 0.9776 and the $F_1$ score of 0.9327 for vehicle classification.