• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.207-211
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• 2011

This paper presents a method for facial feature representation and recognition from the Covariance Matrices of the Gabor-filtered images. Gabor filters are a very powerful tool for processing images that respond to different local orientations and wave numbers around points of interest, especially on the local features on the face. This is a very unique attribute needed to extract special features around the facial components like eyebrows, eyes, mouth and nose. The Covariance matrices computed on Gabor filtered faces are adopted as the feature representation for face recognition. Geodesic distance measure is used as a matching measure and is preferred for its global consistency over other methods. Geodesic measure takes into consideration the position of the data points in addition to the geometric structure of given face images. The proposed method is invariant and robust under rotation, pose, or boundary distortion. Tests run on random images and also on publicly available JAFFE and FRAV3D face recognition databases provide impressively high percentage of recognition.

• Journal of the Semiconductor & Display Technology
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• v.12 no.1
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• pp.1-7
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• 2013

Grey-level statistical models have been widely used in many applications for object location and identification. However, conventional models yield some problems in model refinement when training images are not properly aligned, and have difficulties for real-time recognition of arbitrarily rotated models. This paper presents improved grey-level statistical models that align training images using image or feature matching to overcome problems in model refinement of conventional models, and that enable real-time recognition of arbitrarily rotated objects using efficient hierarchical search methods. Edges or features extracted from a mean training image are used for accurate alignment of models in the search image. On the aligned position and orientation, fitness measure based on grey-level statistical models is computed for object recognition. It is demonstrated in various experiments in PCB inspection that proposed methods are superior to conventional methods in recognition accuracy and speed.

• The Journal of Korean Physical Therapy
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• v.23 no.2
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• pp.77-84
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• 2011

Purpose: This study was designed to investigate the level of recognition and utilization of Korean physical therapists for assistive technology. Methods: The subjects of this study were 218 physical therapists who worked in various institutions in Seoul, Kyonggi-do, and Choongchung area. A questionnaire was developed using a related article. Simple descriptive statistics were used for respondent characteristics, and for the level of recognition and utilization. Results: The physical therapists reported having a less-than-average level of recognition and utilization for assistive technology. They were cognizant that the use of assistive technology devices were used mainly for specific outcome such as mobility, seating and position, and ADL. Conclusion: Our findings indicate that physical therapists need more opportunities for training in assistive technology. For effective clinical applications of assistive technology, there should be continuous support, such as college education, continued education, and related seminars.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.6
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• pp.76-85
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• 1993

In this paper, we propose a stroke matching method for the off-line recognition of handprinted Hangul. In this method, the preprocessing steps such as position normalization, contour tracing and thinning are carried out first. Then, after extracting features such as the firection component distribution of contour, the direction component distribution of skeleton, and the distribution of structural feature points, strokes are extracted and matched based on the midpont distribution of the direction and the length of each stroke. In order to reduce the recognition time, a preliminary classification based on the direction component distribution features of the contour is performed. In order to domonstrate the performance of the proposed method, experiments with 520 most frequently used Hangul were performed, and 90.7% of correct recognition rate and 0.46second of recognition time per one character has been obtained. This results reveal that the proposed method can absorb effectively the noise in input character and the variations of stroke slant.

• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.430-443
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• 2013

The recognition of current position and road surrounding of car is very important to driver for safe driving. This paper presents the recognition technique of the road traveling environment using position information hiding and viewpoint transform that monitors the information of road furniture and signature and notifies them to driver. The proposed scheme generates the road images into which the position information are hided, from car camera and GPS module and provides the road information to driver through the viewpoint transformation and the road signature detection. The driving tests with camera and GPS module verified that the position information hiding takes about 66.5ms per frame, the detection rate of road signature is about 95.83%, and the road signature detection takes about 227.45ms per frame. Therefore, we know that the proposed scheme can recognize the road traveling environment on the road video with 15 frame rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.226-232
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• 2015

As the age of smart device has come, recently many application services related to smart phone are developing. The LBS(Location Based Service) technique is considered as one of the most important techniques to support location based application services. Usually the smart phone acquires the information of position by using the position recognition systems and sensors such as GPS(Global Positioning System) and G-Sensor. However, since the GPS signal from the satellite can hardly be received in the indoor environments, new LBS techniques for the indoor environment are required. In this paper, to solve the problem a position information transceiver using LED lights and smart phone camera sensor is proposed. We proved the possibility of the proposed positioning system through the experiments in the laboratory for the practical verification.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.934-937
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• 2003

In this paper, authors use a stereo vision system based on the visual model of human and establish inexpensive method that recognizes moving distance using characteristic points around the robot. With the stereovision. the changes of the coordinate values of the characteristic points that are fixed around the robot are measured. Self-displacement and self-localization recognition system is proposed from coordination reconstruction with those changes. To evaluate the proposed system, several characteristic points that is made with a LED around the robot and two cheap USB PC cameras are used. The mobile robot measures the coordinate value of each characteristic point at its initial position. After moving, the robot measures the coordinate values of the characteristic points those are set at the initial position. The mobile robot compares the changes of these several coordinate values and converts transformation matrix from these coordinate changes. As a matrix of the amount and the direction of moving displacement of the mobile robot, the obtained transformation matrix represents self-displacement and self-localization by the environment.

• The Journal of the Acoustical Society of Korea
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• v.13 no.5
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• pp.24-31
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• 1994

In this paper, we study continuous speech recognition of Korean language using acoustic models of word juncture coarticulation. To alleviate the performance degradation due to coarticulation problems, we use context-dependent units that model inter-word transitions in addition to intra-word transitions. In all cases the initial phone of each word has to be specified for each possible final phone of the previous word similarly for the final phone of each word. To improve the robustness of the HMM parameters, the covariance matrix is smoothed. We also use position-dependent units to improve the discriminative power between units. Simulation results show that when the improved models of word juncture coarticulation are used. the recognition performance is considerably improved compared to the baseline system using only intra-word units.

• Journal of the Korean Society of Safety
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• v.24 no.3
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• pp.65-70
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• 2009

In-vehicle route guidance information(RGI) systems have been developed with the advancement of the information and communication technologies. However, the RGI is provided by a pre-determined option, drivers occasionally pass the target intersection owing to non- or late- recognizing it. The purpose of this experiment is to examine the position of driver's tum signal operation and intersection recognition approaching at the target intersection which is difficult to identify as a preliminary research on developing the additional RGI connecting with the tum signal control. The field experiment was conducted to measure distances of the turn signal operation and intersection recognition from the target intersection according to driving lanes and landmarks at adjacent intersection. And, glance behavior to the car navigation display was evaluated by using an eye camera. The results indicate that drivers operate the turn signal after confirming a landmark in the case of the intersection with it. However, most case of driving, drivers operate the tum signal at 40 to 50m before coming to the target. To provide the additional RGI, when drivers do not operate the tum signal approaching at the target intersection based on the results, is expected to improve the traffic safety and the comfort for drivers.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.251-256
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• 2019

This paper presents an algorithm for recognizing and tracking a vehicle at a distance using a monocular camera installed at the center of the windshield of a vehicle to operate an autonomous vehicle in a racing. The vehicle is detected using the Haar feature, and the size and position of the vehicle are determined by detecting the shadows at the bottom of the vehicle. The region around the recognized vehicle is determined as ROI (Region Of Interest) and the vehicle shadow within the ROI is found and tracked in the next frame. Then the position, relative speed and direction of the vehicle are predicted. Experimental results show that the vehicle is recognized with a recognition rate of over 90% at a distance of more than 100 meters.