• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.8
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• pp.67-75
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• 2000

In this paper, we proposed a new method to find dive parameters of an ellipse from the optical Hough transform (HT) results. The method employs the HT for detection of a straight line and the one-dimensional analysis of the resultant parameter domain. Using this algorithm, we simulated about the ellipses with different positions, and obtained the information of the ellipse with 94% accuracy in the worst case. To compare the simulation results with the experimental ones, we performed optical experiments using a HT Computer Generated Hologram (CGH) filter. Through the experiments, we showed that our results were very similar to the simulation results.

• Journal of Mechanical Science and Technology
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• v.15 no.3
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• pp.300-308
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• 2001

Tracking of moving objects within video streams is a complex and time-consuming process. Large number of moving objects increases the time for computation of tracking the moving objects. Because of large computations, there are real-time processing problems in tracking of moving objects. Also, the change of environment causes errors in estimation of tracking information. In this paper, we present a new method for tracking of moving objects using optical flow motion analysis. Optical flow represents an important family of visual information processing techniques in computer vision. Segmenting an optical flow field into coherent motion groups and estimating each underlying motion are very challenging tasks when the optical flow field is projected from a scene of several moving objects independently. The problem is further complicated if the optical flow data are noisy and partially incorrect. Optical flow estimation based on regulation method is an iterative method, which is very sensitive to the noisy data. So we used the Combinatorial Hough Transform (CHT) and Voting Accumulation for finding the optimal constraint lines. To decrease the operation time, we used logical operations. Optical flow vectors of moving objects are extracted, and the moving information of objects is computed from the extracted optical flow vectors. The simulation results on the noisy test images show that the proposed method finds better flow vectors and more correctly estimates the moving information of objects in the real time video streams.

• Smart Media Journal
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• v.10 no.4
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• pp.80-90
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• 2021

Using optical music recognition technology based on deep learning, we propose to apply the results derived to VR games. To detect the music objects in the music sheet, the deep learning model used YOLO v5, and Hough transform was employed to detect undetected objects, modifying the size of the staff. It analyzes and uses BPM, maximum number of combos, and musical notes in VR games using output result files, and prevents the backlog of notes through Object Pooling technology for resource management. In this paper, VR games can be produced with music elements derived from optical music recognition technology to expand the utilization of optical music recognition along with providing VR contents.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11
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• pp.3566-3575
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• 2000

In this paper, we propose an simple and efficient method to estunate the camera operation by using compressed information, which is extracted diracily from MPEG2 stream without complete decoding. In the method, the motion vector is converted into approximate optical flow by using the feature of predicted frame, because the motion vector in MPEG2 video stream is not regular sequene. And they are used to estimate the camera operation, which consist of pan, and zoom by Hough transform technique. The method provided better results than the least square method for video stream of basketball and socer games. The proposed method can have a reduced computational complexity because the information is directiv abtained in compressed domain. Additionally it can be a useful technology in content-based searching and analysis of video information. Also, the estimatd cameral operationis applicable in searching or tracking objects in MPEG2 video stream without decoding.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.435-444
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• 2005

This paper presents a lane-departure identification (LDI) algorithm for a traveling vehicle on a structured road. The algorithm makes up for the weak points of the former method based on EDF[1] by introducing a Lane Boundary Pixel Extractor (LBPE), the well known Hough transform, and liner regression. As a filter to extract pixels expected to be on lane boundaries, the LBPE plays an important role in enhancing the robustness of LDI. Utilizing the pixels from the LBPE the Hough transform provides the lane-related parameters composed of orientation and distance, which are used in the LDI. The proposed LDI is based on the fact the lane-related parameters of left and right lane boundaries are symmetrical as for as the optical axis of a camera mounted on a vehicle is coincident with the center of lane; as the axis deviates from the center of lane, the symmetrical property is correspondingly lessened. In addition, the LDI exploits a linear regression of the lane-related parameters of a series of successive images. It plays the key role of determining the trend of a vehicle's traveling direction and minimizing the noise effect. Except for the two lane-related parameters, the proposed algorithm does not use other information such as lane width, a curvature, time to lane crossing, and of feet between the center of a lane and the optical axis of a camera. The system performed successfully under various degrees of illumination and on various road types.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.22 no.12
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• pp.1084-1088
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• 2009

The measurement of dynamic stagger in electric railways is one of the key test parameters to increase speed and maintain safety in electric railways. This paper is introduces a non-contact optical-based measuring instrument of a catenary system in electric railways. The instrument is implemented by utilizing a CCD (Charge Coupled Device) camera installed on the roof of a vehicle for vision acquisition and image processing techniques including the Canny edge detector and the Hough transform to detect contact wires and calculate dynamic stagger. To check the validity of our approach for the intended application, we measured stagger of a overhead wire of a Korea Tilting Train (TTX). The non-contact optical-based measurement system proposed in this paper performs real-time stagger measurement of an activated high-voltage contact wire. By results of this paper, the instrument should be applied to assess performance and reliability of newly developed electric railway vehicles.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.10
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• pp.948-956
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• 2014

Today, Intelligent Vehicle Detection System seeks to reduce the negative factors, such as accidents over to get the traffic information of existing system. This paper proposes detection algorithm for the illegal U-turn vehicles which can cause critical accident among violations of road traffic laws. We predicted that if calculated optical flow vectors were shown on the illegal U-turn path, they would be cause of the illegal U-turn vehicles. To reduce the high computational complexity, we use the algorithm of pyramid Lucas-Kanade. This algorithm only track the key-points likely corners. Because of the high computational complexity, we detect center lane first through the color information and progressive probabilistic hough transform and apply to the around of center lane. And then we select vectors on illegal U-turn path and calculate reliability to check whether vectors is cause of the illegal U-turn vehicles or not. Finally, In order to evaluate the algorithm, we calculate process time of the type of algorithm and prove that proposed algorithm is efficiently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1340-1345
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• 2001

In this paper, we proposed the method computing the optimal solution of Optical Flow(OF) representing the moving information of moving object and improving the operating speed. In order to do that, we computed the optimal solution of OF using the Combinatorial Hough Transform(CHT) and Voting accumulation and simply searched the moving object compared to conventional method.

• Current Optics and Photonics
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• v.1 no.3
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• pp.196-202
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• 2017

Corona discharge is always a sign of failure processes of high-voltage electrical apparatus, including those utilized in electric railway systems. Solar-blind ultraviolet (UV) cameras are effective tools for corona inspection. In this work, we present an automatic railway corona-discharge detection system based on solar-blind ultraviolet detection. The UV camera, mounted on top of a train, inspects the electrical apparatus, including transmission lines and insulators, along the railway during fast cruising of the train. An algorithm based on the Hough transform is proposed for distinguishing the emitting objects (corona discharge) from the noise. The detection system can report the suspected corona discharge in real time during fast cruises. An experiment was carried out during a routine inspection of railway apparatus in Xinjiang Province, China. Several corona-discharge points were found along the railway. The false-alarm rate was controlled to less than one time per hour during this inspection.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.557-557
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• 2000

Tracking of the moving object, which is realized by the computer vision, is used for military and industrial fields. It is the application technique with imply complicated processing for understanding the input images. But, in these days, the most moving object tracking algorithms have many difficult problems. A typical problem is the increase of calculation time depending on target number. For this reason, there are many studies to solve real time processing problems and errors for background environmental change. In this paper, we used optical flow which is one of moving object tracking algorithms. It represents vector of the moving object. Optical flow estimation based on the regularization method depends on iteration method but it is very sensitive the noise. We proposed a new method using the Combinatorial Hough Transform (CHT) and Voting Accumulation in order to find optimal constraint lines. Also, we used the logical operation in order to release the operation time. The proposed method can easily and accurately extract the optical flow of moving object area and the moving information. We have simulated the proposed method using the test images. This images are included the noise. Experimental results show that the proposed method get better flow and estimate accurately the moving information.