• Journal of information and communication convergence engineering
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• v.4 no.3
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• pp.123-129
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• 2006

The limited number of roads and the increasing number of vehicles demand the automatic regulation of overspeed vehicles, illegal vehicles, and overloaded vehicles and the automatic charge calculation depending on the type of the vehicle. To meet such requirements, it is important to remove the shadow of the vehicle as processing and recognizing an image captured by a camera. The shadow of the vehicle is likely to cause misclassification of the vehicle type due to diverse errors and mistakes occurring when detecting geometrical properties of the vehicle. In case that shadows of two different vehicles are overlapped, not only the type of the vehicles may be misclassified but also it is difficult to accurately identify the type of the vehicles. In this paper, we propose a robust algorithm to remove the shadow of a vehicle by calculating the luminance, the chrominance, the gradient density of the cast shadow from information acquired using the image subtraction of the background, and to recognize the substantial vehicle figure. Even when it is hard to detect and split a target vehicle from its shadow as shadows of vehicles are attached to each other, our robust algorithm can detect the vehicle figure only. We implemented our system with a general camera and conducted experiments on various vehicles on general roads to find out our vehicle shade removal algorithm is efficient when detecting and recognizing vehicles.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.161-170
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• 2001

Vehicle detection is the basic of traffic monitoring. Video based systems have several apparent advantages compared with other kinds of systems. However, In video based systems, shadows make troubles for vehicle detection. especially active shadows resulted from moving vehicles. In this paper a new method that combines background subtraction and edge detection is proposed for vehicle detection and shadow rejection. The method is effective and the correct rate of vehicle detection is higher than 98(%) in experiments, during which the passive shadows resulted from roadside buildings grew considerably. Based on the proposed vehicle detection method, vehicle tracking, counting, classification and speed estimation are achieved so that traffic information concerning traffic flow is obtained to describe the load of each lane.

• ETRI Journal
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• v.41 no.4
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• pp.494-505
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• 2019

In this paper, we propose a new framework for detecting the unauthorized dumping of garbage in real-world surveillance camera. Although several action/behavior recognition methods have been investigated, these studies are hardly applicable to real-world scenarios because they are mainly focused on well-refined datasets. Because the dumping actions in the real-world take a variety of forms, building a new method to disclose the actions instead of exploiting previous approaches is a better strategy. We detected the dumping action by the change in relation between a person and the object being held by them. To find the person-held object of indefinite form, we used a background subtraction algorithm and human joint estimation. The person-held object was then tracked and the relation model between the joints and objects was built. Finally, the dumping action was detected through the voting-based decision module. In the experiments, we show the effectiveness of the proposed method by testing on real-world videos containing various dumping actions. In addition, the proposed framework is implemented in a real-time monitoring system through a fast online algorithm.

• The Korean Journal of Nuclear Medicine Technology
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• v.15 no.2
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• pp.60-64
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• 2011

Purpose: The brain perfusion SPECT is the examination which is able to know adversity information related brain disorder. But brain perfusion SPECT has also high failure rates by patient's motions. In this case, we have to use two days method and patients put up with many disadvantages. We think that we don't use two days method in brain perfusion SPECT, if we can use registration method. So this study has led to look over registration method applications in brain perfusion SPECT. Materials and Methods: Jaszczak, Hoffman and cylindrical phantoms were used for acquiring SPECT image data on varying degree in x, y, z axes. The phantoms were filled with $^{99m}Tc$ solution that consisted of a radioactive concentration of 111 MBq/mL. Phantom images were acquired through scanning for 5 sec long per frame by using Triad XLT9 triple head gamma camera (TRIONIX, USA). We painted the ROI of registration image in brain data. So we calculated the ROIratio which was different original image counts and registration image counts. Results: When carring out the experiments under the same condition, total counts differential was from 3.5% to 5.7% (mean counts was from 3.4% to 6.8%) in phantom and patients data. In addition, we also run the experiments in the double activity condition. Total counts differential was from 2.6% to 4.9% (mean counts was from 4.1% to 4.9%) in phantom and patients data. Conclusion: We can know that original and registration data are little different in image analysis. If we use the image registration method, we can improve disadvantage of two days method in brain perfusion SPECT. But we must consider image registration about the distance differences in x, y, z axes.

• Journal of Astronomy and Space Sciences
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• v.22 no.4
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• pp.393-408
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• 2005

We developed and compared two automatic algorithms for moving object detections in the YSTAR-NEOPAT sky survey program. One method, called starlist comparison method, is to identify moving object candidates by comparing the photometry data tables from successive images. Another method, called image subtraction method, is to identify the candidates by subtracting one image from another which isolates sources moving against background stars. The efficiency and accuracy of these algorithms have been tested using actual survey data from the YSTAR-NEOPAT telescope system. For the detected candidates, we performed eyeball inspection of animated images to confirm validity of asteroid detections. Main conclusions include followings. First, the optical distortion in the YSTAR-NEOPAT wide-field images can be properly corrected by comparison with USNO-B1.0 catalog and the astrometric accuracy can be preserved at around 1.5 arcsec. Secondly, image subtraction provides more robust and accurate detection of moving objects. For two different thresholds of 2.0 and $4.0\sigma$, image subtraction method uncovered 34 and 12 candidates and most of them are confirmed to be real. Starlist comparison method detected many more candidates, 60 and 6 for each threshold level, but nearly half of them turned out to be false detections.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.4B
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• pp.353-364
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• 2002

In this paper, a new onto-digital stereo object-tracking system using hierarchical digital algorithms and optical BPEJTC is proposed. This proposed system can adaptively track a moving target by controlling the convergence of stereo camera. firstly, the target is detected through the background matching of the sequential input images by using optical BPEJTC and then the target area is segmented by using the target projection mask which is composed by hierarchical digital processing of image subtraction, logical operation and morphological filtering. Secondly, the location's coordinate of the moving target object for each of the sequential input frames can be extracted through carrying out optical BPEJTC between the reference image of the target region mask and the stereo input image. Finally, the convergence and pan/tilt of stereo camera can be sequentially controlled by using these target coordinate values and the target can be kept in tracking. Also, a possibility of real-time implementation of the adaptive stereo object tracking system is suggested through optically implementing the proposed target extraction and convergence control algorithms.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.3
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• pp.61-69
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• 2010

This paper presents an efficient object selection algorithm by analyzing and detecting of human activity. Generally, when people point any something, they will put a face on the target direction. Therefore, the direction of the face and fingers and was ordered to be connected to a straight line. At first, in order to detect the moving objects from the input frames, we extract the interesting objects in real time using background subtraction. And the judgment of movement is determined by Principal Component Analysis and a designated time period. When user is motionless, we estimate the user's indication by estimation in relation to vector from the head to the hand. Through experiments using the multiple views, we confirm that the proposed algorithm can estimate the movement and indication of user more efficiently.

• Korean Journal of Optics and Photonics
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• v.17 no.4
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• pp.312-316
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• 2006

In this study, a miniature fiber-optic radiation sensor has been developed using a water-equivalent organic scintillator for electron beam therapy dosimetry. The intensity of Cerenkov light is measured and characterized as a function of the incident angle of the electron beam from a LINAC. Also, a subtraction method using a background optical fiber without a scintillator and an optical discrimination method using optical filters are investigated to remove Cerenkov light, which could cause problems or limit the accuracy for detecting a fluorescent light signal in a fiber-optic radiation sensor.

• Journal of Sensor Science and Technology
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• v.15 no.3
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• pp.186-191
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• 2006

In general, Cerenkov light is produced by a charged particle that passes through a medium with a velocity greater than that of visible light. Although the wavelength of Cerenkov light is very broad, the peak is in the almost visible range from 400 to 480 nm. Therefore, it always causes a problem to detect a real light signal that is generated in the scintillator on the fiber-optic sensor tip for dose measurements of high-energy electron beam. The objectives of this study are to measure, characterize and remove Cerenkov light generated in a fiber-optic radiation sensor tip to detect a real light signal from the scintillator. In this study, the intensity of Cerenkov light is measured and characterized as a function of incident angle of electron beam from a LINAC, and as a function of the energy of electron beam. As a measuring device, a photodiode-amplifier system is used, and a subtraction method using a background optical fiber is investigated to remove Cerenkov light.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.319-326
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• 2016

Abnormal situation caused by aggressive behavior of pigs adversely affects the growth of pigs, and comes with an economic loss in intensive pigsties. Therefore, IT-based video surveillance system is needed to monitor the abnormal situations in pigsty continuously in order to minimize the economic demage. In this paper, we propose a new Kinect camera-based monitoring system for the detection of the individual pigs. The proposed system is characterized as follows. 1) The background subtraction method and depth-threshold are used to detect only standing-pigs in the Kinect-depth image. 2) The moving-pigs are labeled as regions of interest. 3) A contour method is proposed and applied to solve the touching-pigs problem in the Kinect-depth image. The experimental results with the depth videos obtained from a pig farm located in Sejong illustrate the efficiency of the proposed method.