• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2365-2370
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• 2017

In this paper, we propose a motion and position recognition technique considering an experiential VR environment. Motion recognition attaches a plurality of AHRS devices to a body part and defines a coordinate system based on this. Based on the 9 axis motion information measured from each AHRS device, the user's motion is recognized and the motion angle is corrected by extracting the joint angle between the body segments. The location recognition extracts the walking information from the inertial sensor of the AHRS device, recognizes the relative position, and corrects the cumulative error using the BLE fingerprint. To realize the proposed motion and position recognition technique, AHRS-based position recognition and joint angle extraction test were performed. The average error of the position recognition test was 0.25m and the average error of the joint angle extraction test was $3.2^{\circ}$.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.423-426
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• 1995

An image processing algorithm is developed in order to recognize the type of cars, the position of a number plate and the characters on the plate. To recognize the type af cars, comparison of two images is used. One has a car image, the other is just a background image without car. After that recognition, a vertical line filter is used to find the location of the plate. Finally the similarity method is used to recognize the numbers on the plates.

• Journal of radiological science and technology
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• v.45 no.5
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• pp.407-412
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• 2022

Cerebral aneurysm coil embolization has the advantages of accurate, low patient burden, and fast recovery time, but efforts are needed to reduce dose due to the burden of exposure radiation dose during interventional procedures. In this study, the area dose product(DAP/Gy·cm²) and fluoro time(min) according to the size of the aneurysm and the location of aneurysm were investigated according to insurance recognition regulations aneurysm classification cerebral aneurysm coil embolization. According to the research method, classification according to the size and location of the aneurysm is first, the size of the aneurysm is divided into less than 4mm, more than 4mm to less than 8mm, and more than 8mm, and second, the dose to the area based on the location site (DAP/Gy·cm²) and fluoro time(min) based on the location site were observed. As a result, the location of the cerebral aneurysm procedure was found to be the Paraclinoid site. During cerebral aneurysm coil embolization, the area dose was 107 Gy·cm² and fluoro time was 47.41 minutes, showing lower results than domestic studies, and when comparing the area dose product with foreign studies, the area dose product results were similar to that of Turkey and Saudi Arabia. It is expected that it can be used as an objective analysis indicator to establish diagnostic reference levels (DRLs) and patient radiation defense guidelines according to the size of cerebral aneurysm and location of cerebral aneurysm procedures during interventional procedures.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.158-163
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• 2010

In this paper, we propose the location measurement algorithm of unknown tag based on RFID (Radio-Frequency IDentification) by using RSSI (Received Signal Strength Indication) and TDOA (Time Difference of Arrival) and extended Kalman filter in smart space. To do this, first, we recognize the location of unknown tag by using the RSSI and TDOA recognition methods. Second, we set the coordinate of the tag location measured by using trilateration and SX algorithm. But the tag location data measured by this method are included complex environmental error. So, we use the extended Kalman filter in order to revise error data of the tag location. Finally, we validate the applicability of the proposed method though the simulation in a complex environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.17-23
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• 2018

The rapid development of mobile technology has increased the use of mobile devices, and the possibility of security incidents is also increasing. The leakage of information through photos is the most representative. Previous methods for preventing this are disadvantageous in that they can not take pictures for other purposes. In this paper, we design and implement a system to prevent information leakage through photos using object recognition and beacon. The system inspects pictures through object recognition based on deep learning and verifies whether security policies are violated. In addition, the location of the mobile device is identified through the beacon and the appropriate rules are applied. Web applications for administrator allow you to set rules for taking photos by location. As soon as a user takes a photo, they apply appropriate rules to the location to automatically detect photos that do not conform to security policies.

• MALSORI
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• no.50
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• pp.99-110
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• 2004

The normal transmission characteristics of sound are hardly obtained due to the various noises and structural factors in a running car environment. It is due to the channel distortion of the original source sound recorded by microphones, and it seriously degrades the performance of the speech recognition in real driving environments. In this paper we analyze the degree of intelligibility under the various sound distortion environments by channels according to driving speed with respect to speech transmission index(STI) and compare the STI with rates of speech recognition. We examine the correlation between measures of intelligibility depending on sound pick-up patterns and performance in speech recognition. Thereby we consider the optimal location of a microphone in single channel environment. In experimentation we find that high correlation is obtained between STI and rates of speech recognition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.459-461
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• 2019

The location estimation algorithm in the existing wireless network uses a base station to estimate the absolute location of three or more in the state where the terminal is fixed. However, this paper suggests a location recognition algorithm that uses a mobile terminal to estimate the location of a mobile base station using a traverse technique using a three-way estimation.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.360-365
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• 2008

We propose an efficient robot name registration and recognition method in order to enable a Call-and-Come service for home robots. In the proposed method for the name registration, the search space is first restricted by using monophone-based acoustic models. Second, the registration of robot names is completed by using triphone-based acoustic models in the restricted search space. Next, the parameter for the utterance verification is calculated to reduce the acceptance rate of false calls. In addition, acoustic models are adapted by using a distance speech database to improve the performance of distance speech recognition, Moreover, the location of a user is estimated by using a microphone array. The experimental result on the registration and recognition of robot names shows that the word accuracy of speech recognition is 98.3%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.241-250
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• 2019

Road signs are guide facilities for road users, and the Ministry of Land, Infrastructure and Transport has established and operated a system to enhance the convenience of managing these road signs. The role of road signs will decrease in the future autonomous driving, but they will continue to be needed. For the accurate mechanical recognition of texts on road signs, automatic road sign recognition equipment has been developed and it has applied image-based text recognition technology. Yet there are many cases of misrecognition due to irregular specifications and external environmental factors such as manual manufacturing, illumination, light reflection, and rainfall. The purpose of this study is to derive location-based destination names for finding misrecognition errors that cannot be overcome by image analysis, and to improve the automatic recognition of road signs destination names by using Levenshtein similarity verification method based on phoneme separation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.84-95
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• 2009

The ubiquitous smart home is the home of the future, which exploits context information from both the human and the home environment, providing an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. In this paper, we present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. The system uses four network cameras for real-time human tracking. This paper explains the architecture of the real-time human tracker, and proposes an algorithm for predicting human location and motion. To detect human location, three kinds of images are used: $IMAGE_1$ - empty room image, $IMAGE_2$ - image of furniture and home appliances, $IMAGE_3$ - image of $IMAGE_2$ and the human. The real-time human tracker decides which specific furniture or home appliance the human is associated with, via analysis of three images, and predicts human motion using a support vector machine (SVM). The performance experiment of the human's location, which uses three images, lasted an average of 0.037 seconds. The SVM feature of human motion recognition is decided from the pixel number by the array line of the moving object. We evaluated each motion 1,000 times. The average accuracy of all types of motion was 86.5%.