• Journal of Korea Multimedia Society
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• v.10 no.6
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• pp.726-736
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• 2007

In this paper, real-time image scanning system using linescan cameras is designed. The system is specially designed to diagnose and analyse the conditions of tunnels such as crack widths through the captured images. The system consists of two major parts, the image acquisition system and the image merging system. To save scanned image data into storage media in real-time, the image acquisition system has been designed with two different control and management modules. The control modules are in charge of controlling the hardware device and the management modules handle system resources so that the scanned images are safely saved to the magnetic storage devices. The system can be mounted to various kinds of vehicles. After taking images, the image merging system generates extended images by combining saved images. Several tests are conducted in laboratory as well as in the field. In the laboratory simulation, both systems are tested several times and upgraded. In the field-testing, the image acquisition system is mounted to a specially designed vehicle and images of the interior surface of the tunnel are captured. The system is successfully tested in a real tunnel with a vehicle at the speed of 20 km/h. The captured images of the tunnel condition including cracks are vivid enough for an expert to diagnose the state of the tunnel using images instead of seeing through his/her eyes.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.8
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• pp.1171-1176
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• 1999

The precision and reliability of the Computer Image Analysis technique using a desk top computer for extracting information from carcass cross section scans was evaluated by the repeatability (R) and coefficient of variation (CV) for error variance. The 6th and 7th ribs cross section of carcasses from 55 fattened Japanese Black steers were used. The image analysis was conducted using a desk top computer (Macintosh-Apple Vision 1710 Display) connected to a scanner and an image capture camera. Two software applications, Adobe Photoshop and Mac Scope were used interchangeably. The information extracted and measured were individual muscle area, circumference length, long and short axes lengths, muscle direction; distance between any two muscle centers of gravity; cross section total area, lean, fat, and bone. The information was extracted after the processes of scanning, digitization, masking, muscle separation, and binarization. When using the Computer Image Analysis technique by desk top computer, proper digitization and selection of scanning resolution are very important in order to obtain accurate information. The R-values for muscle area, circumference, long and axes lengths, and direction ranged from 0.95 to 0.99, whereas those of the distance between any two muscle centers of gravity ranged from 0.96 to 0.99, respectively. For the cross section total area, lean, fat, and bone it ranged from 0.83 to 0.99. Excellent repeatability measurements were observed for muscle direction and distance between any two muscle centers of gravity. The results indicate that the Computer Image Analysis technique using a desk top computer for extracting information from carcass cross section is reliable and has high precision.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.409-418
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• 2003

Object tracking in video is one of subject that computer vision and several practical application field have interest in several years. This paper proposes real time object tracking and face region extraction method that can be applied to security and supervisory system field. For this, in limited environment that camera is fixed and there is seldom change of background image, proposed method detects position of object and traces motion using difference between input image and background image. The system creates adaptive background image and extracts pixels in object using line scan method for more stable object extraction. The real time object tracking is possible through establishment of MBR(Minimum Bounding Rectangle) using extracted pixels. Also, effectiveness for security and supervisory system is improved due to extract face region in established MBR. And through an experiment, the system shows fast real time object tracking under limited environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.636-642
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• 2017

In this paper, We proposed a novel hand-gesture recognition algorithm using concentric-circle expanding and tracing. The proposed algorithm determines region of interest of hand image through preprocessing the original image acquired by web-camera and extracts the feature of hand gesture such as the number of stretched fingers, finger tips and finger bases, angle between the fingers which can be used as intuitive method for of human computer interaction. The proposed algorithm also reduces computational complexity compared with raster scan method through referencing only pixels of concentric-circles. The experimental result shows that the 9 hand gestures can be recognized with an average accuracy of 90.7% and an average algorithm execution time is 78ms. The algorithm is confirmed as a feasible way to a useful input method for virtual reality, augmented reality, mixed reality and perceptual interfaces of human computer interaction.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.279-287
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• 2006

This paper proposes a method to detect fall action by using stereo images to recognize emergency situation. It uses 3D information to extract the visual information for learning and testing. It uses HMM(Hidden Markov Model) as a recognition algorithm. The proposed system extracts background images from two camera images. It extracts a moving object from input video sequence by using the difference between input image and background image. After that, it finds the bounding rectangle of the moving object and extracts 3D information by using calibration data of the two cameras. We experimented to the recognition rate of fall action with the variation of rectangle width and height and that of 3D location of the rectangle center point. Experimental results show that the variation of 3D location of the center point achieves the higher recognition rate than the variation of width and height.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.87-93
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• 2012

In this paper, we proposed a faulty pattern detection algorithm of TCP(Tape Carrier Package)/COF(Chip On Film), and implemented a real-time system for inspecting TCP/COF. Since TCP/COF has very high resolution having several micro meters, the human operator should visually inspect all the parts through microscope. In this work, we implement an inspection system to detect the faulty pattern, so the operator can visually inspect only the designated parts by the inspection system through the monitor. The proposed defects detection algorithm for TCP/COF packages is implemented by the pattern matching method based on subtracting the reference image from test image. To evaluate performance of the proposal system. we made various experiments according to type of CCD camera and light source as well as illumination projection method. From experimental results, it is confirmed that the proposed system makes it possible to detect effectively the defective TCP/COF film.

• Journal of the Korea Computer Graphics Society
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• v.13 no.2
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• pp.55-60
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• 2007

Diminished reality (DR) is a technique that provide a visual convenience by virtually hiding an object. Most of existing DR systems have been implemented based on HMDs or desktop displays. However, Here has been no report on the development of DR system based on projection displays due to technical difficulty in spite of its superiority in the aspect of human factor to conventional displays. Rapid advances of projection displays and projection-based vision technologies motivated us to develop a projection-based DR system. As the first attempt, this paper proposes a projection-based diminished reality system using an image completion technique. Its usefulness is demonstrated through experiments and its potential applications are discussed.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.13-24
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• 2011

This paper deals with a 3D-pose (orientation and position) estimation problem of a circular object in 3D-space. Circular features can be found with many objects in real world, and provide crucial cues in vision-based object recognition and location. In general, as a circular feature in 3D space is perspectively projected when imaged by a camera, it is difficult to recover fully three-dimensional orientation and position parameters from the projected curve information. This paper therefore proposes a 3D pose estimation method of a circular feature using a coplanar point. We first interpret a circular feature with a coplanar point in both the projective space and 3D space. A procedure for estimating 3D orientation/position parameters is then described. The proposed method is verified by a numerical example, and evaluated by a series of experiments for analyzing accuracy and sensitivity.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.4
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• pp.34-40
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• 2008

This paper presents a vision based walking robot control system using hand shape recognition. To recognize hand shapes, the accurate hand boundary needs to be tracked in image obtained from moving camera. For this, we use an active contour model-based tracking approach with mean shift which reduces dependency of the active contour model to location of initial curve. The proposed system is composed of four modules: a hand detector, a hand tracker, a hand shape recognizer and a robot controller. The hand detector detects a skin color region, which has a specific shape, as hand in an image. Then, the hand tracking is performed using an active contour model with mean shift. Thereafter the hand shape recognition is performed using Hue moments. To assess the validity of the proposed system we tested the proposed system to a walking robot, RCB-1. The experimental results show the effectiveness of the proposed system.

• Journal of IKEEE
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• v.14 no.3
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• pp.224-231
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• 2010

Automatic detection of objects in images has been one of core challenges in the areas such as computer vision and pattern analysis. Especially, with the recent deployment of personal mobile devices such as smart phone, such technology is required to be transported to them. Usually, these smart phone users are equipped with devices such as camera, GPS, and gyroscope and provide various services through user-friendly interface. However, the smart phones fail to give excellent performance due to limited system resources. In this paper, we propose a new scheme to improve object recognition performance based on pre-computation and simple local features. In the pre-processing, we first find several representative parts from similar type objects and classify them. In addition, we extract features from each classified part and train them using regression functions. For a given query image, we first find candidate representative parts and compare them with trained information to recognize objects. Through experiments, we have shown that our proposed scheme can achieve resonable performance.