• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.277-282
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• 2011

This paper describes a sensor fusion-based semantic map building which can improve the capabilities of a mobile robot in various domains including localization, path-planning and mapping. To build a semantic map, various environmental information, such as doors and cliff areas, should be extracted autonomously. Therefore, we propose a method to detect doors, cliff areas and robust visual features using a laser scanner and a vision sensor. The GHT (General Hough Transform) based recognition of door handles and the geometrical features of a door are used to detect doors. To detect the cliff area and robust visual features, the tilting laser scanner and SIFT features are used, respectively. The proposed method was verified by various experiments and showed that the robot could build a semantic map autonomously in various indoor environments.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.72-76
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• 2023

The mobile card system used for mobile access control is connected to the door lock mounted on the door, enabling non-contact control. The RSSI (Received Signal Strength Indicator) of the BLE (Bluetooth Low Energy) communication packet used here can help to know the direction and distance of the mobile device. In this study, the desirable access control distance was calculated and implemented by setting the RSSI of the transmitter of the BLE packet used in mobile access control and processing the RSSI of the receiver.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1152-1157
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• 2021

This paper proposes a face recognition method for access control of apartment building. Different from most existing face recognition methods, the proposed one does not require any manual process for face enrollment. When a person is exiting through the main entrance door, his/her face data (i.e., face image and face feature) are automatically extracted from the captured video and registered in the database. When the person needs to enter the building again, the face data are extracted and the corresponding face feature is compared with the face features registered in the database. If a matching person exists, the entrance door opens and his/her access is allowed. The face data of the matching person are immediately deleted and the database has the latest face data of outgoing person. Thus, a higher recognition accuracy could be expected. To verify the feasibility of the proposed method, Python based face recognition has been implemented and the cloud service provided by a web portal.

• Journal of the Korea Furniture Society
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• v.24 no.4
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• pp.400-407
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• 2013

21C modern society is a time when enough design to dominate the world, a unique design is required new in all aspects. In addition, there is a religion to the best of Zen art. In our cultural heritage with a ethnicity unique unparalleled in the world, and a new recognition of traditional culture and identity of its own in our country, lattice door flower temple the beauty of Korea in the way you tell, it was modernized by interpreting a new one to utilize as a design element of a wood lattice door flower temple. In this study, to re-appear in openwork having regard to the symbolism of pattern and shape of the lattice door flower temple molding properties were highlighted, change the part of the motif, repeated the curve geometric has been designed to simplify as. As a result, it is possible to present the possibility of a design element that can design a traditional Korean is reinterpreted Modern thereby simplify the repetitive element of the related art, for a new aesthetic changes unique. Design Development of wood with a Buddhist temple flower lattice modern re-interpretation, it suits while a strong indication Korea imagery and expressed a variety of needs and personality to the design elements that are competitive in the world the cage, and design of wood, various studies competitive on to be applied to each field is required.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.200-204
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• 2008

In this paper, to solve localization problem for out-door navigation of robotic vehicles, a particle filter based 3D object recognition framework that can estimate the pose of a building or its entrance is presented. A particle filter framework of multiple evidence fusion and model matching in a sequence of images is presented for robust recognition and pose estimation of 3D objects. The proposed approach features 1) the automatic selection and collection of an optimal set of evidences 2) the derivation of multiple interpretations, as particles representing possible object poses in 3D space, and the assignment of their probabilities based on matching the object model with evidences, and 3) the particle filtering of interpretations in time with the additional evidences obtained from a sequence of images. The proposed approach has been validated by the stereo-camera based experimentation of 3D object recognition and pose estimation, where a combination of photometric and geometric features are used for evidences.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.11 no.1
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• pp.23-28
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• 2012

In this paper, we proposed and developed a fast and efficient real time face detection and recognition which can be run on embedded system instead of high performance desktop. In the face detection process, we detect a face by finding eye part which is one of the most salient facial features after applying various image processing methods, then in the face recognition, we finally recognize the face by comparing the current face with the prepared face database using a template matching algorithm. Also we optimized the algorithm in our system to be successfully used in the embedded system, and performed the face detection and recognition experiments on the embedded board to verify the performance. The developed method can be applied to automatic door, mobile computing environment and various robot.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.313-316
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• 2002

The need to protect a main information and control a personal access using Biometrics in the intelligent building system is extended with growing the information and communication technologies in recent years. The fingerprint recognition technology is one of the biometrics methods available that has been widely used in various applications. But the present architecture of fingerprint recognition system has many of the problems because of centralized control network architecture. But we can solve the problems with distributed control network architecture. In this paper, the fingerprint recognition system uses the merit of the LonWorks. it is able to easily modularize the system and make up for the weak points in the typical fingerprint recognition system.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.8-14
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• 2020

Recently, there was an increasing demand for an integrated access control system which is capable of user recognition, door control, and facility operations control for smart buildings automation. The market available door lock access control solutions need to be improved from the current level security of door locks operations where security is compromised when a password or digital keys are exposed to the strangers. At present, the access control system solution providers focusing on developing an automatic access control system using (RF) based technologies like bluetooth, WiFi, etc. All the existing automatic door access control technologies required an additional hardware interface and always vulnerable security threads. This paper proposes the user identification and authentication solution for automatic door lock control operations using camera based visible light communication (VLC) technology. This proposed approach use the cameras installed in building facility, user smart devices and IoT open source controller based LED light sensors installed in buildings infrastructure. The building facility installed IoT LED light sensors transmit the authorized user and facility information color grid code and the smart device camera decode the user informations and verify with stored user information then indicate the authentication status to the user and send authentication acknowledgement to facility door lock integrated camera to control the door lock operations. The camera based VLC receiver uses the artificial intelligence (AI) methods to decode VLC data to improve the VLC performance. This paper implements the testbed model using IoT open-source based LED light sensor with CCTV camera and user smartphone devices. The experiment results are verified with custom made convolutional neural network (CNN) based AI techniques for VLC deciding method on smart devices and PC based CCTV monitoring solutions. The archived experiment results confirm that proposed door access control solution is effective and robust for automatic door access control.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.6
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• pp.237-242
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• 2014

Current digital door lock systems are mainly designed for users' convenience, so they have weakness in security. Thus, this paper suggests a video digital doorlock system grouped with a relay device, a server, and a digital doorlock with a camera, sensors, and communication modules, which is detecting or recognizing objects approaching to the front of the door lock system and sending images and door-opening information to users' smart devices. Experiments showed that the suggested system has 96~98% recognition rate of approaching objects and requires 17.1~23.9 seconds for transmission on average, depending on network systems. Therefore, the system is thought to have enough capability for real time security response by monitoring the front area of the doorlock system.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1199-1206
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• 2022

In this paper, unlike door locks that are controlled only by the existing keypad because electronic devices can be easily operated through apps on smartphones in modern society, an app was created using app inventory so that door locks can be controlled using smartphones. Through the Bluetooth module experiment, the communication distance with the smartphone was controlled up to 10m when there were no obstacles, and through the voice recognition experiment, the recognition rate was 85% and 90% at 500~1000Hz and 1000~1500Hz, respectively, and 70% and 80% at 80dB noise. Through the results of the experimental evaluation, it was confirmed that convenience and security could be improved.