• Proceedings of KOSOMES biannual meeting
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• 2005.11a
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• pp.65-69
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• 2005

The theoretical propagation modes of radio waves in the area of Line of Sight(LOS) within Fresnel zone are searched for the available detection ranges in a Marine RFID (Radio Frequency Identification). The structural LOS model to Earth's curvature is proposed and, the calculation method of horizontal distance in a specific radio frequency is also considered in this work As studying results, it is found that the height of antenna to cover the detection ranges and the influences of detection ranges by weather environments can be analyse with the theoretical methods.

• Journal of Korea Multimedia Society
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• v.13 no.9
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• pp.1314-1321
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• 2010

In this paper, we study about the vehicle detection algorithm which is in the process of travelling from the road. An input image is segmented by means of split and merge algorithm. And two largest segmented regions are removed for reducing search region and speed up processing time. In order to detect the back side of the front vehicle considers a vertical/horizontal component, uses an integral image with to apply Haar-like methods which are the possibility of shortening a calculation time, classified with SVM. The simulation result of the method which is proposed appeared highly.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.89-93
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• 2002

This paper introduces a vision-based on-line fabric inspection methodology of woven textile fabrics. Current procedure for determination of fabric defects in the textile industry is performed by human in the off-line stage. The advantage of the on-line inspection system is not only defect detection and identification, but also 벼ality improvement by a feedback control loop to adjust set-points. The proposed inspection system consists of hardware and software components. The hardware components consist of CCD array cameras, a frame grabber and appropriate illumination. The software routines capitalize upon vertical and horizontal scanning algorithms characteristic of a particular deflect. The signal to noise ratio (SNR) calculation based on the results of the wavelet transform is performed to measure any deflects. The defect declaration is carried out employing SNR and scanning methods. Test results from different types of defect and different style of fabric demonstrate the effectiveness of the proposed inspection system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.97-100
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• 2013

In this paper, we propose a detection method of the character rather than cursive, containing many components of the vertical and horizontal direction in complex background image. The characters have many dense corners but the background has few sparse corners. So we use harris corner detector and cluster the corners by using the position of the detected corners for detecting character regions. To merge or filter character regions, we analysis a histogram of gray image of character regions. In each improved region, we compare histograms of R, G, B channels to detect characters.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.490-498
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• 2011

In this paper, we present a two-stage vision-based approach to detect multi views of pedestrian in road scene images. The first stage is HG (Hypothesis Generation), in which potential pedestrian are hypothesized. During the hypothesis generation step, we use a vertical, horizontal edge map, and different colors between road background and pedestrian's clothes to determine the leg position of pedestrian, then a novel symmetry peaks processing is performed to define how many pedestrians is covered in one potential candidate region. Finally, the real candidate region where pedestrian exists will be constructed. The second stage is HV (Hypothesis Verification). In this stage, all hypotheses are verified by Support Vector Machine for classification, which is robust for multi views of pedestrian detection and recognition problems.

• Journal of the Korean Geotechnical Society
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• v.23 no.1
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• pp.51-65
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• 2007

The purpose of this study is the development and application of a high resolution ultrasonic wave imaging system to detect discontinuity plane in lab-scale rock models. This technique is based on received time series which capture the multiple reflections at interface. This study includes the fundamental aspects of ultrasonic wave propagation in rock mass, the selection of the optimal ultrasonic wave transducer, data gathering, a signal processing, imaging methods, and experiments. Experiments are carried out by the horizontal movement and rotation devices. Experimental studies show the discontinuity is well detected by the horizontal movement and rotation devices under water. Furthermore, the discontinuity and the cavity on the plaster block are identified by the rotation device. This study suggests that the new method may be an economical and effective tool for the detection of the discontinuity on rock mass.

• Journal of the Korea Society of Computer and Information
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• v.16 no.9
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• pp.69-76
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• 2011

According to the related reports, about 60 percents of ship collisions have resulted from operating mistake caused by human factor. Specially, the report said that negligence of observation caused 66.8 percents of the accidents due to a human factor. Hence automatic detection and tracking of an object from an IR images are crucial for safety navigation because it can relieve officer's burden and remedies imperfections of human visual system. In this paper, we present a method to detect an object such as ship, rock and buoy from a sea IR image. Most edge directions of the sea image are horizontal and most vertical edges come out from the object areas. The presented method uses them as a characteristic for the object detection. Vertical edges are extracted from the input image and isolated edges are eliminated. Then morphological closing operation is performed on the vertical edges. This caused vertical edges that actually compose an object be connected and become an object candidate region. Next, reference object regions are extracted using horizontal edges, which appear on the boundaries between surface of the sea and the objects. Finally, object regions are acquired by sequentially integrating reference region and object candidate regions.

• Journal of Korea Multimedia Society
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• v.9 no.4
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• pp.470-481
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• 2006

In this paper, we propose a real-time face detection, tracking and tilted face image correction system using multi-color model and face feature information. In the proposed system, we detect face candidate using YCbCr and YIQ color model. And also, we detect face using vertical and horizontal projection method and track people's face using Hausdorff matching method. And also, we correct tilted face with the correction of tilted eye features. The experiments have been performed for 110 test images and shows good performance. Experimental results show that the proposed algorithm robust to detection and tracking of face at real-time with the change of exterior condition and recognition of tilted face. Accordingly face detection and tilted face correction rate displayed 92.27% and 92.70% respectively and proposed algorithm shows 90.0% successive recognition rate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.367-370
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• 2015

This paper proposes an improve method of the detection performance of traffic lights for autonomous driving cars. Earlier detection methods used to adopt color thresholding, template matching and based learning maching methods, but its have some problems such as recognition rate decreasing, slow processing time. The proposed method uses both detection mask and morphological preprocessing. Firstly, input color images are converted to YCbCr image in order to strengthen its illumination, and horizontal edge components are extracted in the Y Channel. Secondly, the region of interest is detected according to morphological characteristics of the traffic lights. Finally, the traffic signal is detected based on color distributions. The proposed method showed that the detection rate and processing time improved rather than the conventional algorithm about some surrounding environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.105-112
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• 2012

Face detection at a distance faces is very challenging since images are often degraded by blurring and noise as well as low resolution. This paper proposes an improved face detection method with AdaBoost filtering and sequential testing stages with color and shape information. The conventional AdaBoost filter detects face regions but often generates false alarms. The face detection method is improved by adopting sequential testing stages in order to remove false alarms. The testing stages comprise skin-color test and variable edge-mask filtering. The skin-color filtering is composed of two steps, which involve rectangular window regions and individual pixels to generate binary face clusters. The size of the variable edge-mask is determined by the ellipse which is estimated from the face cluster. The validation of the horizontal and vertical ratio of the mask is also investigated. In the experiments, the efficacy of the proposed algorithm is proved by images captured by a CCTV and a smart-phone