• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.179-180
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• 1998

In this paper, we propose an algorithm to detect fetal movements using M-mode ultrasonography. To do this work automatically, we find the crosscorrelation between the current data vector of the depth direction of M-mode image and the previous one. In the crosscorrelation estimator, the variations of time lag $\tau$ at maximum crosscorrelation value means fetal movements. A woman in the 37th week of pregnancy was monitored and the ultrasonic image of fetus was recorded over 20-minute period to detect fetal movements using B-mode and M-mode ultrasonography simultaneously. And the presented method was compared with maternal perception and B-mode ultrasonography observed by clinician. The maternal perception method detected only 57% of all fetal movements observed by clinician. The detection of the presented method corresponds to the clinician's detection result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.618-632
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• 2010

This paper presents a novel approach to control the augmented reality (AR) objects robustly in a marker-less AR system by fingertip tracking and hand pattern recognition. It is known that one of the promising ways to develop a marker-less AR system is using human's body such as hand or face for replacing traditional fiducial markers. This paper introduces a real-time method to manipulate the overlaid virtual objects dynamically in a marker-less AR system using both hands with a single camera. The left bare hand is considered as a virtual marker in the marker-less AR system and the right hand is used as a hand mouse. To build the marker-less system, we utilize a skin-color model for hand shape detection and curvature-based fingertip detection from an input video image. Using the detected fingertips the camera pose are estimated to overlay virtual objects on the hand coordinate system. In order to manipulate the virtual objects rendered on the marker-less AR system dynamically, a vision-based hand control interface, which exploits the fingertip tracking for the movement of the objects and pattern matching for the hand command initiation, is developed. From the experiments, we can prove that the proposed and developed system can control the objects dynamically in a convenient fashion.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.1-12
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• 2008

This paper presents automatic moving object detection method using the rotating camera covering larger area with a single camera. The proposed method is based on the edge segment matching which robust to the dynamic environment with illumination change and background movement. The proposed algorithm presents an edge segment based background panorama image generation method minimizing the distortion due to image stitching, the background image generation method using Generalized Hough Transformation which can reliably register the current image to the panorama image overcoming the stitching distortions, the moving edge segment extraction method that overcome viewpoint difference and distortion. The experimental results show that the proposed method can detect correctly moving object under illumination change and camera vibration.

• Journal of Veterinary Clinics
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• v.14 no.2
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• pp.279-286
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• 1997

Serial ultrasonographic examinations were daily performed on 11 bitches (5 Maltese and 3 Yorkshire terrier) from day 15 until parturition to determine the time of Sift detection and ultrasonographic appearance of the fetal and extra-fetal structures. Gestational age was timed from the day of ovulation (day 0), which was estimated to occur when p18sma progesterone concentration was first increased above 4.0 ng/ml. The gestational length in 8 bitches was 61.5 (range: 60-64) days. The initial detection time of fetal and extra-fetal structures were: gestational sac at days 20.5 (18-23); zonary placenta in the uterine wall at days 25.4 (24-30); yolk sac membrane at days 25,5 (23-37); amniotic mombrane at days 28.7 (25-32); embryo initial detection at days 23.3 (20-26); fetal heartbeat at days 23.9 (21-27); fetal movement at days 31.3 (26-34); limb buds at days 32.1 (29-35); rotomarh at days 35.3 (32-40); urinary bladder at days 35.6 (33-39); skeleton at days 37.8 (37- 40) and kidney at days 45.3 (41-49), respectively.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.236-241
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• 2008

This paper presents a method to recognize the plane regions for movement of walking robots. When the autonomous agencies using stereo camera or laser scanning sensor is under unknown 3D environment, the mobile agency has to detect the plane regions to decide the moving direction and perform the given tasks. In this paper, we propose a very fast method for plane detection using normal vector of a triangle by 3 vertices defined on a small circular region. To reduce the effect of noises and outliers, the triangle rotates with respect to the center position of the circular region and generates a series of triangles with different normal vectors based on different three points on the boundary of the circular region. The vectors for several triangles are normalized and then median direction of the normal vectors is used to test the planarity of the circular region. The method is very fast and we prove the performance of algorithm for real range data obtained from a stereo camera system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.119-124
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• 2015

As Location-Based Services (LBSs) of smartphones increases, the power consumption of a smartphone due to Global Positioning System (GPS) is becoming increasingly serious. This paper presents a new location estimation scheme for smartphones called Adaptive Location Detection (ALD). ALD adaptively detects the location of a smartphone considering the movement pattern of a user, category of applications executed in the smartphone, and the battery level. Simulation with various real applications and scenarios show that ALD reduces 37% of energy consumption compared to GPS. Nevertheless, it satisfies the accuracy requirement of each situation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2C
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• pp.78-85
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• 2011

In this paper we proposed an intelligent PTZ camera system which detects, classifies and tracks moving objects. If a moving object is detected, features are extracted for classification and then realtime tracking follows. We used GMM for detection followed by shadow removal. Legendre moment is used for classification. Without auto focusing, we can control the PTZ camera movement by using center points of the image and object's direction, distance and velocity. To implement the realtime system, we used TI DM6446 Davinci processor. Throughout the experiment, we obtained system's high performance in classification and tracking both at vehicle's normal and high speed motion.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.73-78
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• 2016

In wireless sensor networks, sensors have capabilities of sensing and wireless communication, computing power and collect data such as sound, movement, vibration. Sensors need to communicate wirelessly to send their sensing data to other sensors or the base station and so they are vulnerable to many attacks like garbage packet injection that cannot be prevented by using traditional cryptographic mechanisms. To defend against such attacks, a behavior-based attack detection is used in which some specialized monitoring nodes overhear the communications of their neighbors(normal nodes) to detect illegitimate behaviors. It is desirable that the total sensing area of normal nodes covered by monitoring nodes is as large as possible. The previous researches have focused on selecting the monitoring nodes so as to maximize the number of normal nodes(node coverage), which does not guarantee that the area sensed by the selected normal nodes is maximized. In this study, we have developed an algorithm for selecting the monitoring nodes needed to cover the maximum sensing area. We also have compared experimentally the covered sensing areas computed by our algorithm and the node coverage algorithm.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.11
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• pp.1647-1654
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• 2013

Detection performance of the vehicle on the road depends on weather conditions, the shadow by the movement of the sun, or illumination changes, etc. In this paper, a vehicle detection system in conjunction with a robust background estimate algorithm to environment change on the road in daytime is proposed. Gaussian Mixture Model is applied as background estimation algorithm, and also, Adaboost algorithm is applied to detect the vehicle for candidate region. Through the experiments with input videos obtained from a various weather conditions at the same actual road, the proposed algorithm were useful to detect vehicles in the road.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1119-1128
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• 2013

In this paper, we propose an algorithm to detect and track the human face with a GPU-based high speed. Basically the detection algorithm uses the existing Adaboost algorithm but the search area is dramatically reduced by detecting movement and skin color region. Differently from detection process, tracking algorithm uses only depth information. Basically it uses a template matching method such that it searches a matched block to the template. Also, In order to fast track the face, it was computed in parallel using GPU about the template matching. Experimental results show that the GPU speed when compared with the CPU has been increased to up to 49 times.