• Advances in robotics research
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• v.2 no.2
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• pp.141-149
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• 2018

In image processing and robotic applications, two-dimensional (2D) black and white patterned planar markers are widely used. However, these markers are not detectable in low visibility environment and they are not changeable. This research proposes an active and adaptive marker node, which displays 2D marker patterns using light emitting diode (LED) arrays for easier recognition in the foggy or turbid underwater environments. Because each node is made to blink at a different frequency, active LED marker nodes were distinguishable from each other from a long distance without increasing the size of the marker. We expect that the proposed system can be used in various harsh conditions where the conventional marker systems are not applicable because of low visibility issues. The proposed system is still compatible with the conventional marker as the displayed patterns are identical.

• Journal of Sensor Science and Technology
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• v.24 no.1
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• pp.54-61
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• 2015

In recent years, there has been increasing use of automatic surveillance and monitoring systems based on vision sensors. Humans are often the most important target in the systems, but processing human images is difficult due to the small sizes and flexible motions. Particularly, occlusion among pedestrians in camera images brings practical problems. In this paper, we propose a novel method to separate image regions of occluded pedestrians. A camera equipped with a wide angle lens is attached to the ceiling of a building corridor for sensing pedestrians with a wide field of view. The output images of the camera are processed for the human detection, tracking, identification, distortion correction, and occlusion handling. We resolve the occlusion problem adaptively depending on the angles and positions of their heads. Experimental results showed that the proposed method is more efficient and accurate compared with existing methods.

• Journal of Sensor Science and Technology
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• v.22 no.6
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• pp.393-399
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• 2013

We propose a method of sensing the rotation and distance of a camera by using a fisheye lens system as a vision sensor. We estimate the rotation angle of a camera with a modified correlation method by clipping similar regions to avoid symmetry problems and suppressing highlight areas. In order to eliminate the rectification process of the distorted points of a fisheye lens image, we introduce an offline process using the normalized focal length, which does not require the image sensor size. We also formulate an equation for calculating the distance of a camera movement by matching the feature points of the test image with those of the reference image.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.1021-1024
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• 2001

Out of all metal-cutting processes, the hole-making process is the most widely used. It is estimated to be more than 30% of the total metal-cutting process. It is therefore desirable to monitor and detect drill wear during the hole-drilling process. In this paper, the vision system of the sensing methods of drill flank wear on the basis of image processing is used to detect the wear pattern by non-contact and direct method and get the reliable wear information about drill. In image processing of acquired image, median filter is applied for noise removal. The vision flank wear area of the drill was measured. Backpropagation neural networks (BPns) were used for no-line detection of drill wear. The neural network consisted of three layers: input, hidden and output. The input vectors comprised of spindle rotational speed, feed rates, vision flank wear, thrust and torque signals. The output was the drill wear state which was either usable or failure. Drilling experiments with various spindle rotational speed and feed rates were carried out. The learning process was peformed effectively by utilizing backpropagation. The detection of the abnormal states using BPNs achieved 96.4% reliability even when the spindle rotational speed and feedrate were changed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.719-723
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• 1997

The welding automation in ship manufacturing process,especially in the sub-assembly line is considered to be a difficult job because the welding part is too huge, various, unstructured for a welding robot to weld fully automatically. The weld orocess at the sub-assembly line for ship manufacturing is to joint the various stiffener on the base panel. In order to realize automatic robot weld in sub-assembly line, robot have to equip with the sensing system to recognize the position of the parts. In this research,we developed a vision system to detect the position of base panle for sub-assembly line is shipbuilding process. The vision system is composed of one CCD camera attached on the base of robot, 2-500W halogen lamps for active illumination. In the image processing algorithm,the base panel is represented by two set of lines located at its two corner through hough transform. However, the various noise line caused by highlight,scratches and stiffener,roller in conveyor, and so on is contained in the captured image, this nosie can be eliminated by region segmentation and threshold in hough transform domain. The matching process to recognize the position of weld panel is executed by finding patterns in the Hough transformed domain. The sets of experiments performed in the sub-assembly line show the effectiveness of the proposed algorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.6
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• pp.134-140
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• 2008

Preceding vehicle detection is a crucial issue for driver assistance system as well as for autonomous vehicle guidance function and it has to be performed with high reliability to avoid any potential collision. The vision-based preceded vehicle detection systems are regarded promising for this purpose because they require little infrastructure on a highway. However, the feasibility of these systems in passenger car requires accurate and robust sensing performance. In this paper, an preceded vehicle detection system is developed using stereo vision sensors. This system utilizes feature matching, epipoplar constraint and feature aggregation in order to robustly detect the initial corresponding pairs. After the initial detection, the system executes the tracking algorithm for the preceded vehicles including a leading vehicle. Then, the position parameters of the preceded vehicles or leading vehicles can be obtained. The proposed preceded vehicle detection system is implemented on a passenger car and its performances is verified experimentally.

• Journal of Sensor Science and Technology
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• v.17 no.5
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• pp.338-345
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• 2008

Steel bearing balls are important component in machines having moving parts. In this paper we describe a vision-based automatic inspection system designed for sensing defects on the surface of steel bearing balls. The system has a camera looking down over a rail on which balls roll. Two mirrors are installed at both sides of the rail so that the side parts of a ball can be well inspected. The entire ball surface can be sufficiently seen by taking three images at $120^{\circ}$ rotation interval. Defects are detected by thresholding the difference image between an image captured and the reference image of a good ball.

• Smart Structures and Systems
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• v.24 no.6
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• pp.769-781
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• 2019

Dynamic displacement response of civil structures is an important index for in-construction and in-service structural condition assessment. However, accurately measuring the displacement of large-scale civil structures such as high-rise buildings still remains as a challenging task. In order to cope with this problem, a vision-based system with the use of industrial digital camera and image processing has been developed for long-distance, remote, and real-time monitoring of dynamic displacement of supertall structures. Instead of acquiring image signals, the proposed system traces only the coordinates of the target points, therefore enabling real-time monitoring and display of displacement responses in a relatively high sampling rate. This study addresses the in-situ experimental verification of the developed vision-based system on the Canton Tower of 600 m high. To facilitate the verification, a GPS system is used to calibrate/verify the structural displacement responses measured by the vision-based system. Meanwhile, an accelerometer deployed in the vicinity of the target point also provides frequency-domain information for comparison. Special attention has been given on understanding the influence of the surrounding light on the monitoring results. For this purpose, the experimental tests are conducted in daytime and nighttime through placing the vision-based system outside the tower (in a brilliant environment) and inside the tower (in a dark environment), respectively. The results indicate that the displacement response time histories monitored by the vision-based system not only match well with those acquired by the GPS receiver, but also have higher fidelity and are less noise-corrupted. In addition, the low-order modal frequencies of the building identified with use of the data obtained from the vision-based system are all in good agreement with those obtained from the accelerometer, the GPS receiver and an elaborate finite element model. Especially, the vision-based system placed at the bottom of the enclosed elevator shaft offers better monitoring data compared with the system placed outside the tower. Based on a wavelet filtering technique, the displacement response time histories obtained by the vision-based system are easily decomposed into two parts: a quasi-static ingredient primarily resulting from temperature variation and a dynamic component mainly caused by fluctuating wind load.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.159-163
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• 2006

The domestic Remote Sensing field uses mainly Landsat TM image that is used to the monitoring of the wide area. In this study, it is analyzed the land cover change of rural and urban area by time series using satellite images and is proposed the vision for a urban balanced development. It execute an analysis for urban change which is a fundamental data of city planning through the integration of the spatial analysis technique of GIS and Remote Sensing using satellite data

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.10a
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• pp.199-203
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• 2001

It is well know that the interest on the on-line sensing of tool wear is groeing more and more with the aim of controlling machine tools productivity form the point of view of quality and quantity. This paper describes the sensing of the amount of flank wear with vision system. To obtain a proper image He-Ne laser generator is used as the lighting source and obtained image is processed with block processing algorithm and morphological image processing method. By means of this system it is possible to evaluate the parameters of tool wear. Experimental tests performed with this system on an NC lathe have shown good performances here described and discussed.