• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2012-2015
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• 2003

This paper proposes a pose-invariant face recognition method using cylindrical model and stereo camera. We divided this paper into two parts. One is single input image case, the other is stereo input image case. In single input image case, we normalized a face's yaw pose using cylindrical model, and in stereo input image case, we normalized a face's pitch pose using cylindrical model with estimated object's pitch pose by stereo geometry. Also, since we have advantage that we can utilize two images acquired at the same time, we can increase overall recognition rate by decision-level fusion. By experiment, we confirmed that recognition rate could be increased using our methods.

• International Journal of Safety
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• v.7 no.1
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• pp.21-25
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• 2008

The occurrence of a corona is that electrical discharge due to the heterogeneity that occurs when an electrical field is concentrated in an electrode due to a cusp formed on said electrode. Wire treatment at the end of a 154kV dead end clamp for end users accelerates the occurrence of corona, which in turn leads to power loss and noise. In this study, the characteristics of the corona which occurs between porcelain insulators and support clamps of overhead lines used in l54kV power receiving facilities for end users were investigated. The corona, which cannot be identified by one common method, was measured utilizing a UV image camera. A risk assessment for fire damage and its status was suggested. The stress distribution of the electrical field by length of bare wire was suggested by means of the finite element method (FEMLAB). As a result, it was found to affect a porcelain insulators. These results can be utilized for the enhancement of clamp installation and safety in power facilities.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1063-1068
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• 2008

A lens system of a camera module for mobile phones is comprised of the composition and design of various shapes of lens. To improve responses such as the modular transfer function (MTF), a lens system should always be constructed by considering uncertainty that can be caused by manufacturing and assembly error. In this study, tolerance optimization using the Latin Hypercube Sampling (LHS) technique is performed. In order to reduce the computational burden of the tolerance optimization process and decrease the influence from numerical noise effectively, we use the Progressive Quadratic Response Surface Modeling (PQRSM), which is one of Sequential Approximate Optimization (SAO) techniques. Using this method, we achieved optimal tolerance for each lens and obtained reliability for satisfying user‘s requirements. In addition, through the design process the manufacturing and assembly cost of a lens system was reduced.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.681-688
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• 2016

In the intelligent video surveillance, recognizing the moving objects is important issue. However, the conventional moving object recognition methods have some problems, that is, the influence of light, the distinguishing between similar colors, and so on. The recognition methods for the moving objects using depth information have been also studied, but these methods have limit of accuracy because the depth camera cannot measure the depth value accurately. In this paper, we propose a recognition method for the moving objects by using both the depth and the color information. The depth information is used for extracting areas of moving object and then the color information for correcting the extracted areas. Through tests with typical videos including moving objects, we confirmed that the proposed method could extract areas of moving objects more accurately than a method using only one of two information. The proposed method can be not only used in CCTV field, but also used in other fields of recognizing moving objects.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.159-165
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• 2012

The accurate focusing position should be determined for accurate measurements In VMS. Camera lens focusing is an important problem in computer vision and video measuring systems (VMS) that use CCD cameras and high precision XYZ stages. Camera focusing is a very important step in high precision measurement systems that use computer vision technique. The auto focusing process consists of two steps, the focus value measurement step and the exact focusing position determination step. It is suitable for eliminating high frequency noises with lower processing time and without blurring. An automatic focusing technique is applied to measure a crater with a one-dimensional search algorithm for finding the best focus. Throughout this paper, the suggested algorithm for the Auto focusing was combined with the learning. As a result, it is expected that such a combination would be expanded into the system of recognizing voices in a noisy environment.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.658-667
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• 1996

A computer vision system was developed to automatically detect and locate the oyster hinge line, one step in shucking an oyster. The computer vision system consisted of a personal computer, a color frame grabber, a color CCD video camera with a zoom lens, two video monitor, a specially designed fixture to hold the oyster, a lighting system to illuminate the oyster and the system software. The software consisted of a combination of commercially available programs and custom designed programs developed using the Microsoft CTM . Test results showed that the image resolution was the most important variable influencing hinge detection efficiency. Whether or not the trimmed -off-flat-white surface area was dry or wet, the oyster size relative to the image size selected , and the image processing methods used all influenced the hinge locating efficiency. The best computer software and hardware combination used successfully located 97% of the oyster hinge lines tested. This efficienc was achieve using camera field of view of 1.9 by 1.5cm , a 180 by 170 pixel image window, and a dry trimmed -off oyster hinge end surface.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.171-190
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• 1996

Quality evaluation of agricultural products has been a subject of interest to many researches for many years. As a results, several nondestructive techniques for quality evaluation of agricultural products have been developed. These methods are based on the detection of various physical properties that correlate well with certain quality factors of the products. This paper presents an overview of various quality evaluation techniques that are based on one of the following properties : density, firmness , vibration characteristic , X-ray and gamma ray transmission, optical reflectance and transmission , electrical properties, aromatic volatile emission, and nuclear magnetic resonance (NMR). The sophistication of nondestructive methods has evolved rapidly with modern technologies. The use of various modern image acquisition techniques, such as solid state TV camera, line-scan camera, X-ray scanning , ultrasonic scanning and NMR imaging, in conjunction with image-processing te hniques has provided new opportunities for researchers to develop many new and improved techniques for nondestructive quality evaluation of agricultural products.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.149-149
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• 2000

We experimented on AGV driving test with color CCD camera which is setup on it. This paper can be divided into two parts. One is image processing part to measure the condition of the guideline and AGV. The other is part that obtains the reference steering angle through using the image processing parts. First, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, AGV knows the driving conditions of AGV. After then using of those information, AGV calculates the reference steering angle changed by the speed of AGV. In the case of low speed, it focuses on the left/right error values of the guide line. As increasing of the speed of AGV, it focuses on the slop of guide line. Lastly, we are to model the above descriptions as the type of PID controller and regulate the coefficient value of it the speed of AGV.

• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.96-103
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• 2014

Global localization is one of the essential issues for mobile robot navigation. In this study, an indoor global localization method is proposed which uses a Kinect sensor and a monocular upward-looking camera. The proposed method generates an environment map which consists of a grid map, a ceiling feature map from the upward-looking camera, and a spatial feature map obtained from the Kinect sensor. The method selects robot pose candidates using the spatial feature map and updates sample poses by particle filter based on the grid map. Localization success is determined by calculating the matching error from the ceiling feature map. In various experiments, the proposed method achieved a position accuracy of 0.12m and a position update speed of 10.4s, which is robust enough for real-world applications.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.142-145
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• 1997

This paper presents the development of depth extraction algorithm or the 3D Endoscopic Data using a stereo matching method and depth calculation. The purpose of other's algorithms is to reconstruct 3D object surface and make depth map, but a one of this paper is to measure exact depth information on the base of [cm] from camera to object. For this, we carried out camera calibration.