• Journal of Multimedia Information System
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• v.4 no.2
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• pp.79-82
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• 2017

Smoke and fire have different shapes and colours. This article suggests a fully connected system which is used two features using Adaboost algorithm for constructing a strong classifier as linear combination. We calculate the local histogram feature by gradient and bin, local binary pattern value, and projection vectors for each cell. According to the histogram magnitude, this paper applied adapted weighting value to improve the recognition rate. To preserve the local region and shape feature which has edge intensity, this paper processed the normalization sequence. For the extracted features, this paper Adaboost algorithm which makes strong classification to classify the objects. Our smoke detection system based on the proposed approach leads to higher detection accuracy than other system.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.205-215
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• 2013

In digital imaging system, Bayer pattern is widely used and the observed image is degraded by optical blur during image acquisition process. Generally, demosaicing and deblurring process are separately performed in order to convert a blurred Bayer image to a high resolution color image. However, the demosaicing process often generates visible artifacts such as zipper effect and Moire artifacts when performing interpolation across edge direction in Bayer pattern image. These artifacts are emphasized by the deblurring process. In order to solve this problem, this paper proposes a deblurring algorithm combined with edge directional color demosaicing method. The proposed method is consisted of interpolation step and region classification step. Interpolation and deblurring are simultaneously performed according to horizontal and vertical directions, respectively during the interpolation step. In the region classification step, characteristics of local regions are determined at each pixel position and the directionally obtained values are region adaptively fused. Also, the proposed method uses blur model based on wave optics and deblurring filter is calculated by using estimated characteristics of local regions. The simulation results show that the proposed deblurring algorithm prevents the boosting of artifacts and outperforms conventional approaches in both objective and subjective terms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.9
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• pp.2145-2152
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• 2013

Paper manufacturing industries have huge facilities with automatic equipments. Especially, in order to improve the efficiency of the paper manufacturing processes, it is necessary to detect the paper cutting defect effectively and to classify the causes correctly. In this paper, we review the problems of web monitoring system and web inspection system that have been traditionally used in industries for defect detection. Then we propose a novel paper cutting defect detection method based on the local binary pattern analysis and its implementation to mitigate the practical problems in industry environment. The proposed algorithm classifies the defects into edge-type and region-type and then it is shown that the proposed system works stably on the real paper cutting defect detection system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.12
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• pp.1173-1183
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• 2009

In order to reduce the download around the Smart UAV(SUAV) at hovering, flow control using synthetic jet has been performed. Many of the complex tilt rotor flow features are captured including the leading and trailing edge separation, and the large region of separated flow beneath the wing. In order to control the leading edge and trailing edge separation, synthetic jet is located at 0.01c, $0.3c_{flap}$, $0.95c_{flap}$. As non-dimensional frequency, the flow pattern is altered and the rate of drag reduction is changed. The results show that synthetic jets shorten the vortex period and decrease the vortex size by changing local flow structure. By using leading edge jet and trailing edge jet, download is efficiently reduced compared to no control case at hovering mode.

• Advances in concrete construction
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• v.14 no.5
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• pp.317-330
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• 2022

This paper investigated computationally and experimentally the interaction here between a notch as well as a micropore under uniaxial compression. Brazilian tensile strength, uniaxial tensile strength, as well as biaxial tensile strength are used to calibrate PFC2d at first. Then, uniaxial compression test was conducted which they included internal notch and micro pore. Experimental and numerical building of 9 models including notch and micro pore were conducted. Model dimensions of models are 10 cm × 10 cm × 5 cm. Joint length was 2 cm. Joints angles were 30°, 45° and 60°. The position of micro pore for all joint angles was 2cm upper than top of the joint, 2 cm upper than middle of joint and 2 cm upper than the joint lower tip, discreetly. The numerical model's dimensions were 5.4 cm × 10.8 cm. The fractures were 2 cm in length and had angularities of 30, 45, and 60 degrees. The pore had a diameter of 1 cm and was located at the top of the notch, 2 cm above the top, 2 cm above the middle, and 2 cm above the bottom tip of the joint. The uniaxial compression strength of the model material was 10 MPa. The local damping ratio was 0.7. At 0.016 mm per second, it loaded. The results show that failure pattern affects uniaxial compressive strength whereas notch orientation and pore condition impact failure pattern. From the notch tips, a two-wing fracture spreads almost parallel to the usual load until it unites with the sample edge. Additionally, two wing fractures start at the hole. Both of these cracks join the sample edge and one of them joins the notch. The number of wing cracks increased as the joint angle rose. There aren't many AE effects in the early phases of loading, but they quickly build up until the applied stress reaches its maximum. Each stress decrease was also followed by several AE effects. By raising the joint angularities from 30° to 60°, uniaxial strength was reduced. The failure strengths in both the numerical simulation and the actual test are quite similar.

• Journal of the Semiconductor & Display Technology
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• v.10 no.2
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• pp.31-38
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• 2011

This paper introduces a video based traffic monitoring system for detecting vehicles and obstacles on the road. To segment moving objects from image sequence, we adopt the background subtraction algorithm based on the local binary patterns (LBP). Recently, LBP based texture analysis techniques are becoming popular tools for various machine vision applications such as face recognition, object classification and so on. In this paper, we adopt an extension of LBP, called the Diagonal LBP (DLBP), to handle the background subtraction problem arise in vision-based autonomous parking systems. It reduces the code length of LBP by half and improves the computation complexity drastically. An edge based shadow removal and blob merging procedure are also applied to the foreground blobs, and a pose estimation technique is utilized for calculating the position and heading angle of the moving object precisely. Experimental results revealed that our system works well for real-time vehicle localization and tracking applications.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.5
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• pp.228-234
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• 2002

The CO$_2$ laser beam irradiation strengthening of 35kgf/mm$_2$ grade steel sheet is investigated to reduce the weight of bumper beam. The increase of tensile strength is dominated by the number of fully penetrated melting lines. The optimal laser irradiation pattern is obtained by 3-point bending test of hat-type specimens. Laser should be irradiated not only on the center specimen densely in the width direction, but also on the edge densely in the longitudinal direction. Local laser strengthening may be effective for the weight reduction of automobile bumper beam.

• Journal of Multimedia Information System
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• v.3 no.4
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• pp.155-160
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• 2016

The Pulse Coupled Neural Network (PCNN) is a kind of neural network models that consists of spiking neurons and local connections. The PCNN was originally proposed as a model that can reproduce the synchronous phenomena of the neurons in the cat visual cortex. Recently, the PCNN has been applied to the various image processing applications, e.g., image segmentation, edge detection, pattern recognition, and so on. The method for the image matching using the PCNN had been proposed as one of the valuable applications of the PCNN. In this method, the Genetic Algorithm is applied to the PCNN parameter learning for the image matching. In this study, we propose the method of the similar image rating using the PCNN. In our method, the Genetic Algorithm based method is applied to the parameter learning of the PCNN. We show the performance of our method by simulations. From the simulation results, we evaluate the efficiency and the general versatility of our parameter learning method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2109-2123
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• 2017

This paper presents a super-resolution reconstruction method based on sparse representation for two-dimensional bar code images. Considering the features of two-dimensional bar code images, Kirsch and LBP (local binary pattern) operators are used to extract the edge gradient and texture features. Feature extraction is constituted based on these two features and additional two second-order derivatives. By joint dictionary learning of the low-resolution and high-resolution image patch pairs, the sparse representation of corresponding patches is the same. In addition, the global constraint is exerted on the initial estimation of high-resolution image which makes the reconstructed result closer to the real one. The experimental results demonstrate the effectiveness of the proposed algorithm for two-dimensional bar code images by comparing with other reconstruction algorithms.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.3
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• pp.66-76
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• 1995

In this research, a mesh connected VLSI structure is proposed for the real time computation of the generalized Hough transform(GHT). The purpose of the research is to design a generalized Hough transformer that can be realized as a single chip processor. The GHT has been modified to yield a highly parallel structure consisting of simple processing elements(PEs) and communication networks. In the proposed structure, the GHT can be computed by first assigning an image pixel to a PE and performing shift and add operations. The result of the CAD circuit simulation shows that it can be computed in the time proportional to the number of pixels in the pattern. In addition to the Hough transformer, the peak detector has been designed to reduce 1)the number of the I/O operations between the transformer and the host computer and 2) the host computer's burden for peak detection by transmitting only the local peaks detected from the transformed accumulator. It is expected that the proposed single chip Hough transformer with peak detector makes a fast and inexpensive edge based object recognition systems possible for many industrial and military applications.