• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.275-284
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• 2008

With increases in recent security requirements, biometric technology such as fingerprints, faces and iris recognitions have been widely used in many applications including door access control, personal authentication for computers, internet banking, automatic teller machines and border-crossing controls. Finger vein recognition uses the unique patterns of finger veins in order to identify individuals at a high level of accuracy. This paper proposes new device and methods for touchless finger vein recognition. This research presents the following five advantages compared to previous works. First, by using a minimal guiding structure for the finger tip, side and the back of finger, we were able to obtain touchless finger vein images without causing much inconvenience to user. Second, by using a hot mirror, which was slanted at the angle of 45 degrees in front of the camera, we were able to reduce the depth of the capturing device. Consequently, it would be possible to use the device in many applications having size limitations such as mobile phones. Third, we used the holistic texture information of the finger veins based on a LBP (Local Binary Pattern) without needing to extract accurate finger vein regions. By using this method, we were able to reduce the effect of non-uniform illumination including shaded and highly saturated areas. Fourth, we enhanced recognition performance by excluding non-finger vein regions. Fifth, when matching the extracted finger vein code with the enrolled one, by using the bit-shift in both the horizontal and vertical directions, we could reduce the authentic variations caused by the translation and rotation of finger. Experimental results showed that the EER (Equal Error Rate) was 0.07423% and the total processing time was 91.4ms.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.355-361
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• 2006

In large scale environments like airport, museum, large warehouse and department store, autonomous mobile robots will play an important role in security and surveillance tasks. Robotic security guards will give the surveyed information of large scale environments and communicate with human operator with that kind of data such as if there is an object or not and a window is open. Both for visualization of information and as human machine interface for remote control, a 3D model can give much more useful information than the typical 2D maps used in many robotic applications today. It is easier to understandable and makes user feel like being in a location of robot so that user could interact with robot more naturally in a remote circumstance and see structures such as windows and doors that cannot be seen in a 2D model. In this paper we present our simple and easy to use method to obtain a 3D textured model. For expression of reality, we need to integrate the 3D models and real scenes. Most of other cases of 3D modeling method consist of two data acquisition devices. One for getting a 3D model and another for obtaining realistic textures. In this case, the former device would be 2D laser range-finder and the latter device would be common camera. Our algorithm consists of building a measurement-based 2D metric map which is acquired by laser range-finder, texture acquisition/stitching and texture-mapping to corresponding 3D model. The algorithm is implemented with laser sensor for obtaining 2D/3D metric map and two cameras for gathering texture. Our geometric 3D model consists of planes that model the floor and walls. The geometry of the planes is extracted from the 2D metric map data. Textures for the floor and walls are generated from the images captured by two 1394 cameras which have wide Field of View angle. Image stitching and image cutting process is used to generate textured images for corresponding with a 3D model. The algorithm is applied to 2 cases which are corridor and space that has the four wall like room of building. The generated 3D map model of indoor environment is shown with VRML format and can be viewed in a web browser with a VRML plug-in. The proposed algorithm can be applied to 3D model-based remote surveillance system through WWW.

• Journal of Korean Elementary Science Education
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• v.37 no.2
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• pp.206-218
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• 2018

The purpose of this study is to analyze the teaching behaviors and visual attention according to teacher's career in Elementary Science Inquire-based Class. Participants were four elementary school teachers in Seoul. They were all in grade 5 and taught science. According to the experience of elementary science education, two novice teachers and two expert teachers were identified. Participants taught Respiration in the 'Structure and Function of our Body' in the elementary science fifth grade. The mobile eye tracker used in this study is SMI's ETG 2w, which is a binocular tracking system. In addition, a video camera was installed behind the classroom to record the entire class. We recorded all the contents of the recorded video and analyzed the results. In this study, the actual practice time, participant's visual attention, and decentralized attention ability were analyzed by class phase. The results of the study are as follows. First, there was a difference between planned class time and actual practice time. The novice teachers were having difficulty in reconstructing the contents of education, and the expert teachers were reconstructing the curriculum and interacting with the students with high understanding and application of the curriculum. There were many differences between the novice teachers and the expert teachers in the tour guidance to confirm student activities. Second, if we look at the visual attention on the area related to teaching and learning by class phase, the novice teacher concentrates all the steps in a specific area, expert teachers showed an equal visual attention to meaningful areas of teaching and learning activities. Third, there was a statistically significant difference in activities 1-1, 1-2, 2-1, and 2-2 when the participants' decentralized attention ability. Expert teachers frequently checked students' understanding and interests. There was a lot of interaction with students. It is also shown through the decentralized attention ability that the novice teachers concentrate on a specific area, and the expert teachers have a high degree of decentralized attention ability and visual attention evenly.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.301-309
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• 2018

The purpose of this study was to investigate the immediate effect of lumbar support and ischial pad on neck, trunk angle and chest expansion for stroke patients using wheelchair. Fifteen stroke patients were measured repeatedly when a lumbar support using(L support), a Ischial pad using(I Pad), a Lumbar support with ischial pad using(L With I), and non using it(Non using). The measurement of the neck and trunk angle was confirmed using a mobile phone camera, and chest expansion was performed using a tapeline. L With I increased significantly in neck and trunk angle and lower chest expansion than non using. This study shows that simultaneous use of lumbar support and ischial pad for stroke patients using wheelchair can increase the neck and trunk angle, chest expansion immediately. Future studies will need to identify more long-term changes by continuing intervention with more subjects.

• Journal of Food Hygiene and Safety
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• v.34 no.6
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• pp.542-550
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• 2019

To detect Escherichia coli from agri-food and production environments, a device based on IoT (internet of things) technology that can check test results in real time on a mobile phone has been developed. The efficiency of the developed device, which combines an incubator equipped with a UV lamp, a high-resolution camera and software to detect E. coli in the field, was evaluated by measuring the device's temperature, detection limit, and detection time. The device showed a difference between its programmed temperature setting and actual temperature of about 1.0℃. In a detection limit test performed with a single-colony inoculation, a color change to yellow and a florescent signal were detected after 12 and 15 h incubations, respectively. The incubation time also decreased along with increasing bacteria levels. When applying the developed method and device to various samples, including utensils, gloves, irrigation water, seeds, and vegetables, detection rates of E. coli using the device were higher than those of the Korean Food Code method. These results show that the developed protocol and device can efficiently detect E. coli from agri-food production environments and vegetables.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.309-318
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• 2009

The researches on the system that automatically records and retrieves one's everyday life is relatively actively worked recently. These systems, called personal memex or life log, usually entail dedicated devices such as SenseCam in MyLifeBits project. This research paid attention to the digital devices such as mobile phones, credit cards, and digital camera that people use everyday. The system enables a person to store everyday life systematically that are saved in the devices or the deviced-related web pages (e.g., phone records in the cellular phone company) and to refer this quickly later. The data collection agent in the proposed system, called MyMemex, collects the personal life log "web data" using the web services that the web sites provide and stores the web data into the server. The "file data" stored in the off-line digital devices are also loaded into the server. Each of the file data or web data is viewed as a memex event that can be described by 4W1H form. The different types of data in different services are transformed into the memex event data in 4W1H form. The memex event ontology is used in this transform. Users can sign in to the web server of this service to view their life logs in the chronological manner. Users can also search the life logs using keywords. Moreover, the life logs can be viewed as a diary or story style by converting the memex events to sentences. The related memex events are grouped to be displayed as an "episode" by a heuristic identification method. A result with high accuracy has been obtained by the experiment for the episode identification using the real life log data of one of the authors.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.64-69
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• 2015

Place awareness is an essential for location-based services that are widely provided to smartphone users. However, traditional GPS-based methods are only valid outdoors where the GPS signal is strong and also require symbolic place information of the physical location. In this paper, environmental sounds and images are used to recognize important aspects of each place. The proposed method extracts feature vectors from visual, auditory and location data recorded by a smartphone with built-in camera, microphone and GPS sensors modules. The heterogeneous feature vectors were then learned by an ensemble learning method that learns each group of feature vectors for each classifier respectively and votes to produce the highest weighted result. The proposed method is evaluated for place recognition using a data group of 3000 samples in six places and the experimental results show a remarkably improved recognition accuracy when using all kinds of sensory data comparing to results using data from a single sensor or audio-visual integrated data only.

• Korean Journal of Optics and Photonics
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• v.12 no.3
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• pp.240-249
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• 2001

A high speed ultra-compact lens with a diffractive optical element (DOE) is designed, which can be applied to mobile communication devices such as IMT2000, PDA, notebook computer, etc. The designed hybrid lens has sufficiently high performance of less than f/2.2, compact size of 3.3 mm (1st surf. to image), and wide field angle of more than 30 deg. compared with the specifications of a single lens. By proper choice of the aspheric and DOE surface which has very large negative dispersion, we can correct chromatic and high order aberrations through the optimization technique. From Seidel third order aberration theory and Sweatt modeling, the initial data and surface configurations, that is, the combination condition of the DOE and the aspherical surface are obtained. However, due to the consideration of diffraction efficiency of a DOE, we can choose only four cases as the optimization input, and present the best solution after evaluating and comparing those four cases. On the other hand, we also report dramatic improvement in optical performance by inserting another refractive lens (so-called, field flattener), that keeps the refractive power of an original DOE lens and makes the petzval sum zero in the original DOE lens system. ystem.

• Journal of Digital Convergence
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• v.14 no.2
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• pp.183-190
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• 2016

This paper proposes algorithm to reduce the computing time in a neural network that reduces transmission of data for tracking mobile objects in surveillance networks in terms of detection and communication load. Object Detection can be defined as follows : Given image sequence, which can forom a digitalized image, the goal of object detection is to determine whether or not there is any object in the image, and if present, returns its location, direction, size, and so on. But object in an given image is considerably difficult because location, size, light conditions, obstacle and so on change the overall appearance of objects, thereby making it difficult to detect them rapidly and exactly. Therefore, this paper proposes fast and exact object detection which overcomes some restrictions by using neural network. Proposed system can be object detection irrelevant to obstacle, background and pose rapidly. And neural network calculation time is decreased by reducing input vector size of neural network. Principle Component Analysis can reduce the dimension of data. In the video input in real time from a CCTV was experimented and in case of color segment, the result shows different success rate depending on camera settings. Experimental results show proposed method attains 30% higher recognition performance than the conventional method.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.722-727
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• 2010

This paper is presented to study simplification of face image using cubic spline interpolation for a business card with 2D barcode. People often forget business card's owner because business cards don't be included a face picture generally. To solve such problem, many applications have be developed through mobile devices, Internet and so on. But they couldn't caught up with value of existing business card mad by paper. Hence, some methods which can put information on business card using 1D or 2D barcode had suggested. but they couldn't include information like face image or company logo image which have too much data. Therefore, we study the simplification method of face image to encode from a face image to 2D barcode. The simplification method using spline curves defined by feature points which we dotted on face, ears, hair, eyebrows, nose, lips, neck, etc.. on a face area. for experiment, we see real face image and simplified face image made by proposed method after we automatically extract face watch through camera. In experimental results, data of simplified face image was reduced as small as it can be expressed by 2D barcode, and confirmed that it can effectively express features.