• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.115-121
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• 2016

Recently, it has become an important problem to extract semantic objects from videos, which are useful for improving the performance of video compression and video retrieval. In this thesis, an automatic extraction method of moving objects of interest in video is suggested. We define that an moving object of interest should be relatively large in a frame image and should occur frequently in a scene. The moving object of interest should have different motion from camera motion. Moving object of interest are determined through spatial continuity by the AMOS method and moving histogram. Through experiments with diverse scenes, we found that the proposed method extracted almost all of the objects of interest selected by the user but its precision was 69% because of over-extraction.

• Journal of Biosystems Engineering
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• v.19 no.4
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• pp.380-396
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• 1994

A personal computer based color machine vision system with video camera and fluorescent lighting system was used to generate images of stationary tobacco leaves. Image processing algorithms were developed to extract both the geometric and the color features of tobacco leaves. Geometric features include area, perimeter, centroid, roundness and complex ratio. Color calibration scheme was developed to convert measured pixel values to the standard color unit using both statistics and artificial neural network algorithm. Improved back propagation algorithm showed less sum of square errors than multiple linear regression. Color features provide not only quality evaluation quantities but the accurate color measurement. Those quality features would be useful in grading tobacco automatically. This system would also be useful in measuring visual features of other agricultural products.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.50-59
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• 2014

This paper proposes a method of localization of vehicle especially the horizontal position for the purpose of recognizing the driving lane. Through tracking road signs, the relative position between the vehicle and the sign is calculated and the absolute position is obtained using the known information from the regulation for installation. The proposed method uses Kalman filter for road sign tracking and analyzes the motion using the pinhole camera model. In order to classify the road sign, ORB(Oriented fast and Rotated BRIEF) features from the input image and DB are matched. From the absolute position of the vehicle, the driving lane is recognized. The Experiments are performed on videos from the highway driving and the results shows that the proposed method is able to compensate the common GPS localization errors.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.7-7
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• 2000

This paper describes a mirror control system that can adjust the location of side and room mirror of the vehicle automatically using 3D coordinates to monitor the location of driver's eyes. Through analysis of the image inputted by two B/W CCD camera and infrared lamps installed on top of the driver's dashboard, we can estimate the values of 3D coordinate of the driver's eyes. Using these values, this system can determine the absolute position of each mirror and activate each actuator to the appropriate position. The stereo vision system can detect the driver's eyes whether it is day or night by virtue of infrared Lamps. We have tested this system using 10 drivers who drive a car currently, and most of the drivers were satisfied with the convenience of this system.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.302-302
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• 2000

This paper presents the measurement and correction of PCB alignment errors for PCB-manufacturing machines. The conventional PCB-manufacturing machine doesn't have enough accuracy to accommodate the demand for high-resolution circuit pattern and high-density mounting capacity of electronic chips. It is because of alignment errors of PCB loaded to the PCB-manufacturing machine. Therefore, this study focuses on the development of the system which is able to measure and correct alignment errors whit high-accuracy. An automatic optical inspection part measures the PCB alignment error using two cameras, and the high-accuracy 3-axis stage makes correct of these error. The operating system is run in the environment of Window 98 (or NT). Finally we implemented this system to PCB screen printer and PCB exposure system.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.77-77
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• 2000

The shape of small or curved object is usually reconstructed using a single camera by moving its lens position to find a sequence of the focused images. Most conventional methods have used a window with fixed shape to test the focus measure, which resulted in a deterioration of accuracy. To solve this problem, this paper proposes a new approach of using a shape adaptive window. It estimates the shape of the object at every step and applies the same shape of window to calculate the focus measure. Focus measure is based on the variance of the pixels inside the window. This paper includes the experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.276-276
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• 2000

This paper presents the efficient algorithms for the pose determination of a circular object with and without a priori knowledge of the object radius. The developed algorithms valid for a circular object are the result of the elaboration of Ma's work [2], which determines the pose of a conic object from two perspective views. First, the geometric constraint of a circular object and its projection on the image plane of a camera is described. The number of perspective views required for the object pose determination with and without a priori knowledge of the object radius is also discussed. Second, with a priori knowledge of the object radius, the pose of a circular object is determined from a single perspective view. The object pose information, expressed by two surface normal vectors and one position vector, is given in a closed form and with no ambiguity. Third, without a priori knowledge of the object radius, the pose of a circular object is determined from two perspective views. While the surface normal vectors are obtained from the first view, the position vector is obtained from the two views.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.3
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• pp.291-295
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• 2012

In the industrial field, real-time monitoring system like a fault early detection is very important. For this, the infrared thermography technique as a new diagnosis method is proposed. This study is focused on the damage detection and temperature characteristic analysis of ball bearing using the non-destructive infrared thermography method. In this paper, thermal image and temperature data were measured by a Cedip Silver 450 M infrared camera. Based on the results, the temperature characteristics under the conditions of normal, loss lubrication, damage, dynamic loading, and damage under loading were analyzed. It was confirmed that the infrared technique is very useful for the detection of the bearing damage.

• Laser Solutions
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• v.13 no.2
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• pp.17-23
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• 2010

It is very important to track a complicate weld seam for the welding automation. Very recently, laser vision sensor becomes a useful sensing tool to find the seams. Until now, however studies of welding automation using a laser vision sensor, focused on either image processing or feature recognition from CCD camera. Even though it is possible to use a simple algorithm for tracking a simple seam, it is extremely difficult to develop a seam-tracking algorithm when the seam is more complex. To overcome these difficulties, this study introduces a simulation system to develop the seam tracking algorithm. This method was verified experimentally to reduce the time and effort to develop the seam tracking algorithm, and to implement the sensing device.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.369-371
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• 2012

Shadow detection and elimination is a critical issue in vision-based system to improve the detection performance of moving objects. However, traditional algorithms are useless at night time because they used the chromaticity and brightness information from the color image sequence. To obtain the high detection performance, we can use the thermal camera and there are shadows by the heat not the light. We proposed a novel algorithm to detect and eliminate the shadows using the thermal intensity and the locality property. By combining two results of the intensity-based and locality-based, we can detect the shadows by the heat and improve the detection performance of moving object.