• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1547-1556
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• 2009

In this paper, we propose a flame detection method using region expansions and on-line variances in outdoor infrared video sequences. To segment flame candidates' regions in infrared images, we first, extract initial regions by high threshold values in infrared images and then the segmented regions are expanded to their neighbors with similar high intensity values. The segmented regions could be non-flame areas like bare-grounds and buildings. Therefore, to detect flame regions in the segmented regions, the segmented regions which have high intensity values in infrared image, are tracked using bounding regions in frame sequences. Variances in the tracked regions are calculated effectively by on-line updates to measure intensity variations on the tracked regions. Experiments show that the proposed method, which is based on region expansions and the average of on-line variances in the regions, is efficient to detect flames in infrared image.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.2
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• pp.171-179
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• 2010

Effective monitoring and maintenance operation of towers, power lines and other defects to ensure high quality and reliability of electric power supplied to customers is becoming one of the most important tasks of today's power industry. One specific technology that has the potential to automate the entire surveillance process is unmanned aerial vehicles. In this paper, we propose a new power line extraction method using the directivity of a power line and Hough transform to detect efficiently power lines from thermal aerial images. In simulation results for several aerial images, the proposed method shows good performance in extracting power line detection.

• Journal of Power Electronics
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• v.10 no.2
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• pp.203-209
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• 2010

This paper describes the development of a three-phase line-interactive DVR with a new sag detection algorithm. The developed detection algorithm has a hybrid structure composed of an instantaneous detector and RMS-variation detectors. The source voltage passes through the sliding-window DFT and RMS calculator, and the instantaneous sag detector. If an instantaneous sag is detected, the RMS variation detector-1 is selected to calculate the RMS variation. The RMS variation detector-2 is selected when the instantaneous sag occurs under the operation of the RMS variation detector-1. The feasibility of the proposed algorithm is verified through computer simulations and experimental work with a prototype of a line-interactive DVR with a 3kVA rating. The line-interactive DVR with the proposed algorithm can compensate for an input voltage sag or an interruption within a 2ms delay. The developed DVR can effectively compensate for a voltage sag or interruption in sensitive loads, such as computers, communications equipment, and automation equipment.

• Journal of Sensor Science and Technology
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• v.20 no.3
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• pp.178-186
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• 2011

Line tracking is a well defined method of mobile robot navigation. It is simple in concept, technically easy to implement, and already employed in many industrial sites. Among several different line tracking methods, magnetic sensing is widely used in practice. In comparison, vision-based tracking is less popular due mainly to its sensitivity to surrounding conditions such as brightness and floor characteristics although vision is the most powerful robotic sensing capability. In this paper, a vision-based robust path line detection technique is proposed for the navigation of a mobile robot assuming uncontrollable surrounding conditions. The technique proposed has four processing steps; color space transformation, pixel-level line sensing, block-level line sensing, and robot navigation control. This technique effectively uses hue and saturation color values in the line sensing so to be insensitive to the brightness variation. Line finding in block-level makes not only the technique immune from the error of line pixel detection but also the robot control easy. The proposed technique was tested with a real mobile robot and proved its effectiveness.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.4
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• pp.173-179
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• 2012

In this paper, we presents a new method for vehicle number plate detection. Our method is basically the method extracting a rectangles from a car image because the shape of a vehicle number plate is a rectangle. For detecting the vehicle number plate, firstly, the contrast of the input image is enhanced. Then, the lines in the image are obtained by using LSD(line segment detector), and rectangles in the image are detected from the line data. These rectangles are the candidates of the car plate, from which the car plate is selected. In this procedure, the method of detecting rectangles is our proposed method, which consists of three stages: (1) extracting corners from the line segments by LSD; (2) extracting diagonal lines from the corner data; and (3) detecting rectangles from diagonal line information. And finally the vehicle number plate is selected from these rectangles by using the feature of the vehicle number plate and the inside information of rectangles. In the experiments with the 100 images captured by our digital camera, we have achieved a detection rate of 94%.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.1
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• pp.70-78
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• 2004

This paper presents study of efficiency of wavelet transformation for on-line chatter detection during hard fuming process. From comparison with other time series and statistical methods such as fast fourier transformation (FFT), Kurtosis and standard deviation (STD), wavelet transform is better than others in on-line chatter detection. With using wavelet function with pseudo frequency corresponding to chatter frequency, chatter could be detected more sensitively. And for both force signal from dynamometer and displacement signal from capacitance type cylindrical sensor (CCS), wavelet transform with DB2 function on level 4 could be well used for chatter detection in hard turning process.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.665-668
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• 2000

This paper presents development of a different substance monitoring system base reliable detection between the conveyer belt and hopper used lot materials transport line of steel company. Conventional detection method of a piece of iron separation system is losed the confidence, because of the place with bad surroundings of measurement so much that materials Production line are completely exposed to dust, moisture and vibration. For the solution of this problem, we developed a different substance detection system using the acoustic emittion sensor and one chip microprocessor which is available for bad surroundings and inexpensive. The reliability of the system was estimated by experiment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.64-73
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• 2011

This paper presents an algorithm for tracking lanes on the road based on corner detection techniques. The proposed algorithm shows high accuracy regardless of lane divider types, eg, solid line, dashed line, etc, and thus is of advantage to city streets and local roads where various types of lane dividers are used. A set of experiments was conducted on real roads with various types of lane dividers and results show an extract ratio over 87% in average.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.4
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• pp.803-808
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• 2000

This paper presents development of a different substance monitoring system base reliable detection between the conveyer belt and hopper used for materials transport line of steel company. Conventional detection method of a piece of iron separation system is losed the confidence, because of the place with bad surroundings of measurement so much that materials production line are completely exposed to dust, moisture and vibration. For the solution of this problem, we developed a different substance detection system using the acoustic emittion sensor and one chip microprocessor which is available for bad surroundings and inexpensive. The reliability of the system was estimated by experiment.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.2
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• pp.103-111
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• 2002

Out of all metal-cutting process, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. One important aspect in controlling the drilling process is monitoring drill wear status. There are two systems, Basic system and Online system, to detect the drill wear. Basic system comprised of spindle rotational speed, feed rates, thrust torque and flank wear measured by tool microscope. Outline system comprised of spindle rotational speed feed rates, AE signal, flank wear area measured by computer vision, On-line monitoring system does not need to stop the process to inspect drill wear. Backpropagation neural networks (BPNs) were used for on-line detection of drill wear. The output was the drill wear state which was either usable or failure. This paper deals with an on-line drill wear monitoring system to fit the detection of the abnormal tool state.