• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_1
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• pp.529-536
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• 2007

Registration between image and object space is a fundamental step in photogrammetry and computer vision. Along with rapid development of sensors - multi/hyper spectral sensor, laser scanning sensor, radar sensor etc., the needs for registration between different sensors are ever increasing. There are two important considerations on different sensor registration. They are sensor invariant feature extraction and correspondence between them. Since point to point correspondence does not exist in image and laser scanning data, it is necessary to have higher entities for extraction and correspondence. This leads to modify first, existing mathematical and geometrical model which was suitable for point measurement to line measurements, second, matching scheme. In this research, linear feature is selected for sensor invariant features and matching entity. Linear features are incorporated into mathematical equation in the form of extended collinearity equation for registration problem known as photo resection which calculates exterior orientation parameters. The other emphasis is on the scheme of finding matched entities in the aide of RANSAC (RANdom SAmple Consensus) in the absence of correspondences. To relieve computational load which is a common problem in sampling theorem, deterministic sampling technique and selecting 4 line features from 4 sectors are applied.

• Journal of Power System Engineering
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• v.10 no.4
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• pp.139-146
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• 2006

In this paper vector code correlation(VCC) method and an algorithm to promote the image processing performance in building an effective measurement system using cameras are described for automatically berthing and controlling the ship equipped with side thrusters. In order to realize automatic ship berthing, it is indispensable that the berthing assistant system on the ship should continuously trace a target in the berth to measure the distance to the target and the ship attitude, such that we can make the ship move to the specified location. The considered system is made up of 4 apparatuses compounded from a CCD camera, a camera direction controller, a popular PC with a built in image processing board and a signal conversion unit connected to parallel port of the PC. The object of this paper is to reduce the image processing time so that the berthing system is able to ensure the safety schedule against risks during approaching to the berth. It could be achieved by composing the vector code image to utilize the gradient of an approximated plane found with the brightness of pixels forming a certain region in an image and verifying the effectiveness on a commonly used PC. From experimental results, it is clear that the proposed method can be applied to the measurement system for automatic ship berthing and has the image processing time of fourfold as compared with the typical template matching method.

• Journal of Korea Multimedia Society
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• v.11 no.2
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• pp.228-236
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• 2008

Recently augmented reality technology has been researched to view the virtual shape of buildings before construction or cultural heritages under recovery. Those researches used special devices or markers that are not applicable in long distanced outdoor environment. Also the server had to compute a lot of transformations for the location changes of virtual objects. This paper proposed a mobile augmented reality system that uses GPS and accelerometer sensors in order to compute the virtual object's locations without using markers. The server determines the position and orientation by comparing the GPS data obtained from the client with the predefined 3D object informations in the server. If the server sends the virtual object informations such as the position, orientation and matching information, then the client matches the virtual object on the screen of mobile camera phone. In addition, the client computes the transformations of location change detected by the accelerometer derived from the user's movement without additional connection to the server.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.4 s.119
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• pp.398-407
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• 2007

In this paper we proposed the tag antenna with a low performance distortion from an attached surface material using the asymmetric dual-arm dipole antenna(ADDA) structure. The tag is designed to exhibit low performance changes when the tag is attached on a target object(the medical litter receptacle, ${\varepsilon}_r=1.7,\;tan\;{\delta}=0.002$). Detail design parameters for the proposed antenna are optimized to maintain a good readable range in free-space as well as on a target object. The size of the optimized antenna is $100\;mm{\times}50\;mm$. The antenna shows the matching bandwidth($S_{11}$< -10 dB) of 3.7 % and the radiation efficiency of 80 % at the operating frequency. Finally we confirmed the readable range of the tag antenna by measurement and it shows about 5.3 m in free space and 5.5 m on the target object.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.851-859
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• 2011

In this paper, we propose the method that automatically extracts the silhouette and the joints of consecutive input image, and track joints to trace object for interaction between human and computer. Also the proposed method presents the action of human being to map human body using joints. To implement the algorithm, we model human body using 14 joints to refer to body size. The proposed method converts RGB color image acquired through a single camera to hue, saturation, value images and extracts body's silhouette using the difference between the background and input. Then we automatically extracts joints using the corner points of the extracted silhouette and the data of body's model. The motion of object is tracted by applying block-matching method to areas around joints among all image and the human's motion is mapped using positions of joints. The proposed method is applied to the test videos and the result shows that the proposed method automatically extracts joints and effectively maps human body by the detected joints. Also the human's action is aptly expressed to reflect locations of the joints

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.153-162
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• 2012

In this paper, we propose a new shape similarity measure for M:N polygon pairs regardless of different object cardinalities in the pairs. The proposed method compares the projections of two shape functions onto Zernike polynomial basis functions, where the shape functions were obtained from each overall region of objects, thus not being affected by the cardinalities of object pairs. Moments with low-order basis functions describe global shape properties and those with high-order basis functions describe local shape properties. Therefore several moments up to a certain order where the original shapes were similarly reconstructed can efficiently describe the shape properties thus be used for shape comparison. The proposed method was applied for the building objects in the New address digital map and a car navigation map of Seoul area. Comparing to an overlapping ratio method, the proposed method's similarity is more robust to object cardinality.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.52-58
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• 2007

In this paper we propose a new robust method to extract accurate human silhouettes indoors with active stereo camera. A prime application is for gesture recognition of mobile robots. The segmentation of distant moving objects includes many problems such as low resolution, shadows, poor stereo matching information and instabilities of the object and background color distributions. There are many object segmentation methods based on color or stereo information but they alone are prone to failure. Here efficient color, stereo and image segmentation methods are fused to infer object and background areas of high confidence. Then the inferred areas are incorporated in graph cut to make human silhouette extraction robust and accurate. Some experimental results are presented with image sequences taken using pan-tilt stereo camera. Our proposed algorithms are evaluated with respect to ground truth data and proved to outperform some methods based on either color/stereo or color/contrast alone.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.839-846
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• 2016

Bin picking is a task of picking a small object from a bin. For accurate bin picking, the 3D pose information, position, and orientation of a small object is required because the object is mixed with other objects of the same type in the bin. Using this 3D pose information, a robotic gripper can pick an object using exact distance and orientation measurements. In this paper, we propose a 3D vision technique for accurate measurement of 3D position and orientation of small objects, on which a paper label is stuck to the surface. We use a maximally stable extremal regions (MSERs) algorithm to detect the label areas in a left bin image acquired from a stereo camera. In each label area, image features are detected and their correlation with a right image is determined by a stereo vision technique. Then, the 3D position and orientation of the objects are measured accurately using a transformation from the camera coordinate system to the new label coordinate system. For stable measurement during a bin picking task, the pose information is filtered by averaging at fixed time intervals. Our experimental results indicate that the proposed technique yields pose accuracy between 0.4~0.5mm in positional measurements and $0.2-0.6^{\circ}$ in angle measurements.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.359-368
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• 2002

In this paper, we propose effective boundary line extraction algorithm for moving objects by matching error image and moving vectors, and fast tracking algorithm for moving object by partial boundary lines. We extracted boundary line for moving object by generating seeds with probability distribution function based on Watershed algorithm, and by extracting boundary line for moving objects through extending seeds, and then by using moving vectors. We processed tracking algorithm for moving object by using a part of boundary lines as features. We set up a part of every-direction boundary line for moving object as the initial feature vectors for moving objects. Then, we tracked moving object within current frames by using feature vector for the previous frames. As the result of the simulation for tracking moving object on the real images, we found that tracking processing of the proposed algorithm was simple due to tracking boundary line only for moving object as a feature, in contrast to the traditional tracking algorithm for active contour line that have varying processing cost with the length of boundary line. The operations was reduced about 39% as contrasted with the full search BMA. Tracking error was less than 4 pixel when the feature vector was $(15\times{5)}$ through the information of every-direction boundary line. The proposed algorithm just needed 200 times of search operation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.10-21
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• 2008

The present paper propose a real-time moving object recognition and tracking method using the wavelet-based neural network and invariant moments. Candidate moving region detection phase which is the first step of the proposed method detects the candidate regions where a pixel value changes occur due to object movement based on the difference image analysis between continued two image frames. The object recognition phase which is second step of proposed method recognizes the vehicle regions from the detected candidate regions using wavelet neurual-network. From object tracking Phase which is third step the recognized vehicle regions tracks using matching methods of wavelet invariant moments bases to recognized object. To detect a moving object from image sequence the candidate regions detection phase uses an adaptive thresholding method between previous image and current image as result it was robust surroundings environmental change and moving object detections were possible. And by using wavelet features to recognize and tracking of vehicle, the proposed method decrease calculation time and not only it will be able to minimize the effect in compliance with noise of road image, vehicle recognition accuracy became improved. The result which it experiments from the image which it acquires from the general road image sequence and vehicle detection rate is 92.8%, the computing time per frame is 0.24 seconds. The proposed method can be efficiently apply to a real-time intelligence road traffic surveillance system.