• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1202-1205
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• 2005

This paper describes a method for vision-based person identification that can detect, track, and recognize person from video using multiple cues: height and dressing colors. The method does not require constrained target's pose or fully frontal face image to identify the person. First, the system, which is connected to a pan-tilt-zoom camera, detects target using motion detection and human cardboard model. The system keeps tracking the moving target while it is trying to identify whether it is a human and identify who it is among the registered persons in the database. To segment the moving target from the background scene, we employ a version of background subtraction technique and some spatial filtering. Once the target is segmented, we then align the target with the generic human cardboard model to verify whether the detected target is a human. If the target is identified as a human, the card board model is also used to segment the body parts to obtain some salient features such as head, torso, and legs. The whole body silhouette is also analyzed to obtain the target's shape information such as height and slimness. We then use these multiple cues (at present, we uses shirt color, trousers color, and body height) to recognize the target using a supervised self-organization process. We preliminary tested the system on a set of 5 subjects with multiple clothes. The recognition rate is 100% if the person is wearing the clothes that were learned before. In case a person wears new dresses the system fail to identify. This means height is not enough to classify persons. We plan to extend the work by adding more cues such as skin color, and face recognition by utilizing the zoom capability of the camera to obtain high resolution view of face; then, evaluate the system with more subjects.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.45-50
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• 2004

In this paper, we propose a new PCA-based LDA Mixture Algorithm(PLMA) for real-time face recognition system. This system greatly consists of the two parts: 1) face extraction part; 2) face recognition part. In the face extraction part we applied subtraction image, color filtering, eyes and mouth region detection, and normalization method, and in the face recognition part we used the method mixing PCA and LDA in extracted face candidate region images. The existing recognition system using only PCA showed low recognition rates, and it is hard in the recognition system using only LDA to apply LDA to the input images as it is when the number of image pixels ire small as compared with the training set. To overcome these shortcomings, we reduced dimension as we apply PCA to the normalized images, and apply LDA to the compressed images, therefore it is possible for us to do real-time recognition, and we are also capable of improving recognition rates. We have experimented using self-organized DAUface database to evaluate the performance of the proposed system. The experimental results show that the proposed method outperform PCA, LDA and ICA method within the framework of recognition accuracy.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.9-18
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• 2020

In the field of image processing, a method of detecting and counting passengers as moving objects when getting on and off the bus has been studied. Among these technologies, one of the artificial intelligence techniques, the deep learning technique is used. As another method, a method of detecting an object using a stereo vision camera is also used. However, these techniques require expensive hardware equipment because of the computational complexity of used to detect objects. However, most video equipments have a significant decrease in computational processing power, and thus, in order to detect passengers on the bus, there is a need for an image processing technology suitable for various equipment using a relatively low computational technique. Therefore, in this paper, we propose a technique that can efficiently obtain the number of passengers on the bus by detecting the contour of the object through the background subtraction suitable for low-cost equipment. Experiments have shown that passengers were counted with approximately 70% accuracy on lower-end machines than those equipped with stereo vision camera.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.73-81
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• 2011

In this paper, an improved block-based background modeling technique using adaptive parameter estimation that judiciously adjusts the number of model histograms at each frame sequence is proposed. The conventional block-based background modeling method has a fixed number of background model histograms, resulting to false negatives when the image sequence has either rapid illumination changes or swiftly moving objects, and to false positives with motionless objects. In addition, the number of optimal model histogram that changes each type of input image must have found manually. We demonstrate the proposed method is promising through representative performance evaluations including the background modeling in an elevator environment that may have situations with rapid illumination changes, moving objects, and motionless objects.

• Journal of Digital Contents Society
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• v.18 no.2
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• pp.383-392
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• 2017

This paper introduces a real-time 3D model generation system that can process in real time from multi-view image acquisition to image-based 3D model generation. This system describes how to collect, transmit, and manage the HD images input from 18 cameras and explain the background separation and smooth 3D volume model generation process. This paper proposes a new distributed data transmission and reception method for real-time processing of HD images input from 18 cameras. In addition, we describe a codebook-based background separating algorithm and a modified marching cube algorithm using perspective difference interpolation to generate smooth 3D models from multi-view images. The system is currently being built with a throughput rate of 30 frames per second.

• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.625-635
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• 2005

In this paper, we propose a hybrid approach for segmenting the lungs efficiently and automatically in chest CT images. The proposed method consists of the following three steps. first, lungs and airways are extracted by two- and three-dimensional automatic seeded region growing and connected component labeling in low-resolution. Second, trachea and large airways are delineated from the lungs by two-dimensional morphological operations, and the left and right lungs are identified by connected component labeling in low-resolution. Third, smooth and accurate lung region borders are obtained by refinement based on image subtraction. In experiments, we evaluate our method in aspects of accuracy and efficiency using 10 chest CT images obtained from 5 patients. To evaluate the accuracy, we Present results comparing our automatic method to manually traced borders from radiologists. Experimental results show that proposed method which use connected component labeling in low-resolution reduce processing time by 31.4 seconds and maximum memory usage by 196.75 MB on average. Our method extracts lung surfaces efficiently and automatically without additional processing like hole-filling.

• Korean Journal of Cognitive Science
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• v.18 no.2
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• pp.159-178
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• 2007

Lee & Kang (2002) showed that simultaneous phonological rehearsal significantly delayed the performance of multiplication but not subtraction, whereas holding an image in the memory delayed subtraction but not multiplication. This result indicated that arithmetic function is related to working memory in a subsystem-specific manner. The aim of the current study was to examine the neural correlates of previous finding using fMRI. For this goal, dual task conditions that required suppression or no suppression were manipulated. In general, several areas were more activated in the interference conditions than in the less interference conditions, although both conditions were dual condition. More important finding is that the specific areas activated in the phonological suppression rendition were right inferior frontal gyrus, left angular, and inferior parietal lobule, while the areas activated in the other condition were mainly in the right superior temporal gyrus and anterior cingulate gyrus. Furthermore, the areas activated in the phonological or visual less suppression condition were right medial frontal gyrus, left middle frontal gyrus, and bilateral medial frontal gyri, anterior cingulate cortices, and parahippocampal gyri, respectively. These results revealed that sharing the processing code invokes interference, and its neural basis.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.159-166
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• 2008

Video image processing systems (VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on a wide-area detection algorithm provide traffic parameters such as flow and velocity as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. However, unlike human vision, VIPS cameras have difficulty in recognizing vehicle movements over a detection zone longer than 100 meters. Over such a distance, the camera operators need to zoom in to recognize objects. As a result, vehicle tracking with a single camera is limited to detection zones under 100m. This paper develops a methodology capable of monitoring individual vehicle trajectories based on image processing. To improve traffic flow surveillance, a long distance tracking algorithm for use over 200m is developed with multi-closed circuit television (CCTV) cameras. The algorithm is capable of recognizing individual vehicle maneuvers and increasing the effectiveness of incident detection.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.25 no.1
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• pp.51-70
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• 1995

The purpose of this investigation was to compare the direct digital radiographic system with film-based digital imaging system using Ektaspeed and Ektaspeed Plus film with respect to image characteristics and detectability and evaluate the sensor noise with the use of subtraction method. Direct digital radiographic system which used was Sens-A-Ray system(Regam Medical Systems, Sundsvall, Sweden) and film-based digital imaging system was composed of Macintosh II ci computer, high resolution Sony XC-77 CCD camera and intraoral x-ray film(Kodak Ektaspeed film, Kodak Ektaspeed Plus film). Images were taken by using CCD sensor of Sens-A-Ray system, Ektaspeed film and Ektaspeed Plus film with variable exposure time(0.06s, 0.1s, 0.16s, 0.2s, 0.3s, 0.4s, 0.5s, 0.6s, O.8s, LOs), 5 times at each exposure time. And then ektaspeed films and ektaspeed plus films were digitized using CCD camera. Image groups were divided into 3 groups; Sens-A-Ray group(direct digital radiographic system), Ektaspeed group and Ektaspeed Plus group (film-based digital imaging system) They were assessed by the following three aspects; image density, image contrast and detectability and sensor noise of Sens-A-Ray system was also evaluated. The results were as follow : 1. S group showed higher density than E , EP group except at the low exposure time(p<0.01). 2. S group showed higher contrast than E,EP group except at the high exposure time(p<0.01). 3. All groups showed good detectability at the each proper exposure time. Lowest exposure time which shows maximum detectability in S,EP group(0.5s) was lower than that in E group(0.6s). 4. Sensor noise of Sens-A-Ray system generally increased according to exposure time. On the basis of the above results, it was considered that Sens-A-Ray system could show higher speed, higher contrast than Ektaspeed, Ektaspeed Plus film except at too high and low exposure time and the same detectability as the conventional intraoral film.

• Progress in Medical Physics
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• v.10 no.2
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• pp.63-71
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• 1999

For the purpose of utilization in 3-D conformal radiotherapy and whole body radiosurgery, the Whole Body 3-Dimensional Topographic Radiation Therapy System has been developed. Whole body frame was constructed in order to be installed on the couch. Radiopaque catheters were engraved on it for the dedicated coordinate system and a MeV-Green immobilizer was used for the patient setup by the help of side panels and plastic rods. By designing and constructing the whole body frame in this way, geometrical limitation to the gantry rotation in 3-D conformal radiotherapy could be minimized and problem which radiation transmission may be altered in particular incident angles was solved. By analyzing CT images containing information of patient setup with respect to the whole body frame, localization and coordination of the target is performed so that patient setup error may be eliminated between simulation and treatment. For the verification of setup, the change of patient positioning is detected and adjusted in order to minimize the setup error by means of comparison of the body outlines using 3 CCTV cameras. To enhance efficiency of treatment procedure, this work can be done in real time by watching the change of patient setup through the monitor. The method of image subtraction in IDL (Interactive Data Language) was used to visualize the change of patient setup. Rotating X-ray system was constructed for detecting target movement due to internal organ motion. Landmark screws were implanted either on the bones around target or inside target, and variation of target location with respect to markers may be visualized in order to minimize internal setup error through the anterior and the lateral image information taken from rotating X-ray system. For CT simulation, simulation software was developed using IDL on GUI(Graphic User Interface) basis for PC and includes functions of graphic handling, editing and data acquisition of images of internal organs as well as target for the preparation of treatment planning.