• Journal of Internet Computing and Services
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• v.12 no.3
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• pp.119-129
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• 2011

Vision-based Human computer interaction is an emerging field of science and industry to provide natural way to communicate with human and computer. Especially, recent increasing demands for mobile augmented reality require the development of efficient interactive technologies between the augmented virtual object and users. This paper presents a novel approach to construct marker-less mobile augmented reality object and control the object. Replacing a traditional market, the human hand interface is used for marker-less mobile augmented reality system. In order to implement the marker-less mobile augmented system in the limited resources of mobile device compared with the desktop environments, we proposed a method to extract an optimal hand region which plays a role of the marker and augment object in a realtime fashion by using the camera attached on mobile device. The optimal hand region detection can be composed of detecting hand region with YCbCr skin color model and extracting the optimal rectangle region with Rotating Calipers Algorithm. The extracted optimal rectangle region takes a role of traditional marker. The proposed method resolved the problem of missing the track of fingertips when the hand is rotated or occluded in the hand marker system. From the experiment, we can prove that the proposed framework can effectively construct and control the augmented virtual object in the mobile environments.

• Proceedings of the Acoustical Society of Korea Conference
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• 1985.10a
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• pp.47-49
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• 1985

In most of ultrasonic NDT(Non-Destructive Testing) equipments using A-scan display technic, it is one of the inconveniences that the user must be proficient in reading the displayed signals for the accurate decisions. In this study, a simple microprocessorized NDT machine for the flaw detection was developed. The operation of system is based on the conventional NDT system. The microprocessor detects the time delay between transmitted pulse and echos by counter-measure method. Then according to the scanning position, the location of flaw orthe other side of testing object is plotted on the CRT. The main advantages of the developed system are simplicity in handling, recording capability of measured data, and low cost.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.652-657
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• 1991

Up to date, application areas of mobile robots have been expanded. In addition, Many types of LRF(Laser Range Finder) systems have been developed to acquire three dimensional information about unknown environments. However in real world, because of various noises (sunlight, fluorescent light), it is difficult to separate reflected laser light from these noise. To overcome the previous restriction, we have developed a new type vision system which enables a mobile robot to measure the distance to a object located 1-5 (m) ahead with an error than 2%. The separation and detection algorithm used in this system consists of pulse phase difference method and multi-stripe structured light. The effectiveness and feasibility of the proposed vision system are demonstrated by 3-D maps of detected objects and computation time analysis.

• International Journal of Contents
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• v.8 no.1
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• pp.16-22
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• 2012

In this paper we propose a method for verifying video in a video telephony system implemented in DM6446 DaVinci Processor. Each frame is categorized either error free frame or error frame depending on the predefined criteria. Human face is chosen as a basic means for authenticating the video frame. Skin color based algorithm is implemented for detecting the face in the video frame. The video frame is classified as error free frame if there is single face object with clear view of facial features (eyes, nose, mouth etc.) and the background of the image frame is not different then the predefined background, otherwise it will be classified as error frame. We also implemented the image histogram based NCC (Normalized Cross Correlation) comparison for video verification to speed up the system. The experimental result shows that the system is able to classify frames with 90.83% of accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.205-208
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• 2006

The position tracking of moving image for surveillance system is presented in this paper. The image of objects moving is detected with difference image between the background image not to be moved relatively and the forward moving image. The moving image is tracked with edge detection and moving vector to the object. The experiment result shows that the system enable to trail the position of moving objects obviously and is able to discriminate an infiltration.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.396-399
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• 2003

This paper proposes a simple digital image stabilization(DIS) algorithm for roll motion, which has not been compensated in the 2-axes mechanical stabilization system, using aero-crossing of the rotational motion vectors. The 2-axes stabilization system cannot stabilize rolled images, which causes the deteriorated performance of the object detection and recognition. In this paper, we propose the rotational motion stabilization algorithm which estimates and compensates global motion in terms of rotational center and rotational angle. Both the synthetic images with undesirable rotational disturbance and the real images from 2-axes stabilization system are used to evaluate the proposed algorithm. The results show that our proposed algorithm suppresses the undesirable rotational disturbance effectively.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.99-106
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• 2009

Though edge detection, an important stage that significantly affecting the performance of image recognition, has been given numerous researches on its execution methods, it still remains as difficult problem and it is one of the components for image recognition applications while it is not the only way to identify an object or track a specific area. This paper, unlike gradient operator using edge detection method, found out edge pixel by referring to 2 neighboring pixels information in binary image and comparing them with pre-defined 4 edge pixels pattern, and detected binary image edge by determining the direction of the next edge detection exploring pixel and proposed method to detect binary image edge by repeating step of edge detection to detect another area edge. When recognizing image, if edge is detected with the use of gradient operator, thinning process, the stage next to edge detection, can be omitted, and with the edge detection algorithm executing time reduced compared with existing area edge tracing method, the entire image recognizing time can be reduced by applying real-time image recognizing system.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.107-116
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• 2015

In compliance with digital device growth, the proliferation of high-tech computers, the availability of high quality and inexpensive video cameras, the demands for automated video analysis is increasing, especially in field of intelligent monitor system, video compression and robot vision. That is why object tracking of computer vision comes into the spotlight. Tracking is the process of locating a moving object over time using a camera. The consideration of object's scale, rotation and shape deformation is the most important thing in robust object tracking. In this paper, we propose a robust object tracking scheme using Random Forest. Specifically, an object detection scheme based on region covariance and ZNCC(zeros mean normalized cross correlation) is adopted for estimating accurate object location. Next, the detected region will be divided into five regions for random forest-based learning. The five regions are verified by random forest. The verified regions are put into the model pool. Finally, the input model is updated for the object location correction when the region does not contain the object. The experiments shows that the proposed method produces better accurate performance with respect to object location than the existing methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.50-53
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• 2022

Recently, there have been cases in which counterfeit foreign ships have entered and left domestic ports several times. Vessels have a ship-specific serial number given by the International Maritime Organization (IMO) to identify the vessel, and IMO marking is mandatory on all ships built since 2004. In the case of airports and ports, which are representative logistics platforms, a security system is essential, but it is difficult to establish a security system at a port and there are many blind spots, which can cause security problems due to insufficient security systems. In this paper, a port security system is designed using deep learning object recognition and OpenCV. The security system process extracts the IMO number of the ship after recognizing the object when entering the ship, determines whether it is the same ship through feature point matching for ships with entry records, and stores the ship image and IMO number in the entry/exit DB for the first arrival vessel. Through the system of this paper, port security can be strengthened by improving the efficiency and system of port logistics by increasing the efficiency of port management personnel and reducing incidental costs caused by unauthorized entry.

• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.73-82
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• 2011

The location-based service is emerging again to the public attention. The location recognition environment up-to-now has been studied with its focus only on a person, an object or a moving object. However, this study proposes a location recognition model that serves to recognize and track, in real time, multiple passengers in a moving vehicle. Identifying the locations of passengers can be classified into two classes: one is to use the high price terminal with GPS function, and the other is to use the economic price compact terminal without GPS function. Our model enables the simple compact terminal to provide effective location recognition under the on-boarding situation by transmitting messages through an interface device and sensor networks for a vehicle equipped with GPS. This technology reduces transmission traffic after detecting the condition of a vehicle (being parked or running), because it does not require transmission/receiving of information on the locations of passengers who are confined in a vehicle when the vehicle is running. Also it extends battery life by saving power consumption of the compact terminal. Hence, we carried out experiments to verify its serviceability by materializing the efficient tracking system for passengers with the detection algorithm of a stopping vehicle proposed in this study. Moreover, about 200 experiments using the system designed with this technology proved successful recognition on on-boarding and alighting of passengers with the maximum transmission distance of 12 km. In addition to this, the running recognition tests showed the test with the detection algorithm of a stopping vehicle has reduced transmission traffic by 41.6% compared to the algorithm without our model.