• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.87-94
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• 2005

3D positional information of lane can be automatically calculated tv combining GPS data, IMU data if coordinates of lane centers are given. The Road Safety Survey and Analysis Vehicle(RoSSAV) is currently under development to analyze three dimensional safety and stability of roads. RoSSAV has GPS and IMU sensors to get positional information of the vehicle and two road-facing CCD cameras for extraction of lane coordinates. In this paper, we develop technology that automatically detects centers of lanes from the road-facing cameras of RoSSAV. The proposed algorithm defines line-support regions by grouping pixels with similar edge orientation and magnitude together and extracts a line from each line support region by planar fitting. Then if extracted lines and the region in-between satisfy the criteria of brightness and width, we decide this region as lane. The proposed algorithm was more precise and stable than the previously proposed algorithm based on brightness threshold method. Experiments with real road scenes confirmed that lane was effectively extracted by the proposed algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.5
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• pp.442-450
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• 2011

A measurement system using stereo pattern recognition (SPR) method was configured to measure the rotor blade deformations and motions. An SPR-based measurement system was prepared using six stereo cameras. Through a series of experiments to evaluate the system measurement uncertainty, it was verified that the SPR system had less than 0.2mm standard uncertainty. The combined standard uncertainties for the lead-lag, flapping, and pitching motions were estimated as 0.296mm, 0.209mm, and $0.238^{\circ}$, respectively. The SPR system was installed at a general small-scaled rotor test system at Korea Aerospace Research Institute. The blade motions and elastic deformation were successfully measured under the conditions with rotating speeds of 360rpm or 589rpm, and collective pitch angles of $0^{\circ}$, $4^{\circ}$, or $6^{\circ}$. The advantages of the SPR system was analyzed in comparison with the measurement system used in Higher Harmonic Control Aeroacoustic Rotor Test -II.

• Journal of Engineering Education Research
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• v.13 no.6
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• pp.171-179
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• 2010

In this paper, we describe a case study of a new lab. project that improves efficiency for education and interest on learning in image processing and pattern recognition related subjects by using LEGO Mindstorms. In addition we verify the validity with analysis of the practical application. LEGO Mindstorms is already used in many educational institution of several countries since about 10 years ago and various case studies have been published. The use of LEGO Mindstorms is generally positive but the negative comments about this exist. The main cause of negative opinion is from unpredictability. The unpredictability from mainly analog characteristics of robot can degrade the effective learning. The describing lab. project suppresses occurrence of unpredictability by minimizing dependence on robots. Students can concentrate on learning the related algorithms by minimizing the learning content and further consideration.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.125-137
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• 2011

Recently the research on the system using images taken from camera phones as input is actively conducted. This paper proposed a system that shows wine pictures which are similar to the input wine label in order. For the calculation of the similarity of images, the representative color of each cell of the image, the recognized text color, background color and distribution of feature points are used as the features. In order to calculate the difference of the colors, RGB is converted into CIE-Lab and the feature points are extracted by using Harris Corner Detection Algorithm. The weights of representative color of each cell of image, text color and background color are applied. The image similarity is calculated by normalizing the difference of color similarity and distribution of feature points. After calculating the similarity between the input image and the images in the database, the images in Database are shown in the descent order of the similarity so that the effort of users to search for similar wine labels again from the searched result is reduced.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.155-164
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• 2011

APP based on the smart phone is being utilized to various scopes such as medical services in hospitals, financing services at banks and credit card companies, and ubiquitous technologies in companies and homes etc. In this service environment, exposures of smart phones cause loss of assets including leaks of official/private information by outsiders. Though secret keys, pattern recognition technologies, and single image authentication techniques are being applied as protective methods, but they have problems in that accesses are possible by utilizing static key values or images like pictures. Therefore, this study proposes a face authentication technology for protecting smart phones from these dangerous factors and problems. The proposed technology authenticates users by extracting key frames of user's facial images by real time, and also controls accesses to the smart phone. Authentication information is composed of multiple key frames, and the user' access is controlled by distinction algorism of similarity utilizing DC values of image's pixel and luminance.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.4
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• pp.607-616
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• 2014

Face recognition is a big challenge in surveillance system since different rotation angles of the face make the difficulty to recognize the face of the same person. This paper proposes a novel method to recognize face with different head poses by using 3D information of the face. Firstly, head pose estimation (estimation of different head pose angles) is accomplished by the POSIT algorithm. Then, 3D face image data is constructed by using head pose estimation. After that, 2D image and the constructed 3D face matching is performed. Face verification is accomplished by using commercial face recognition SDK. Performance evaluation of the proposed method indicates that the error range of head pose estimation is below 10 degree and the matching rate is about 95%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.480-483
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• 2018

In this paper, we study the interference canceling and image sensing processing technology of multiple light sources for high speed transmission in CMOS sensor based visible light communication system. To improve transmission capacity in optical camera communications via image sensors, different data must be transmitted simultaneously from each LED. However, multiple LED light source environments for high-speed transmission can cause interference between adjacent LEDs. In this case, since the visible light communication system generally uses intensity modulation, when a plurality of LEDs transmit data at the same time, it is difficult to accurately detect the respective LEDs due to the light scattering interference of the adjacent LEDs. In order to solve this problem, the ON / OFF state of many LEDs of the light source is accurately recognized by using a dual CMOS sensor, and the spectral estimation technique and the pixel image signal processing technique of each LED are proposed. This technique can accurately recognize multiple LED pixels and improve the total average bit error rate and throughput of a MISO-VLC system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.331-339
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• 2016

This paper developed a home wellness robot platform to perform the roles in basic health care and life care in an aging society. A robotic platform and a sensory platform were implemented for an indoor wellness service. In the robotic platform, the precise mobility and the dexterous manipulation are not only developed in a symbiotic service-robot, but they also ensure the robot architecture of human friendliness. The mobile robot was made in the agile system, which consists of Omni-wheels. The manipulator was made in the anthropomorphic system to carry out dexterous handwork. In the sensing platform, RF tags and stereo camera were used for self and target localization. They were processed independently and cooperatively for accurate position and posture. The wellness robot platform was integrated in a real-time system. Finally, its good performance was confirmed through live indoor tests for health and life care.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.155-161
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• 2021

Gesture recognition analytics through a camera in real time have been widely studied in recent years. Since a small number of features from human joints are extracted, low accuracy of classifying models is get in conventional gesture recognition studies. In this paper, CBAM (Convolutional Block Attention Module) with high accuracy for classifying images is proposed as a classification model and algorithm calculating the angle of joints depending on actions is presented to solve the issues. Employing five exercise gestures images from the fitness posture images provided by AI Hub, the images are applied to the classification model. Important 8-joint angles information for classifying the exercise gestures is extracted from the images by using MediaPipe, a graph-based framework provided by Google. Setting the features as input of the classification model, the classification model is learned. From the simulation results, it is confirmed that the exercise gestures are classified with high accuracy in the proposed model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.463-465
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• 2021

Currently, the inspection method printed on food packages and boxes is to sample only a few products and inspect them with human eyes. Such a sampling inspection has the limitation that only a small number of products can be inspected. Therefore, accurate inspection using a camera is required. This paper proposes a deep learning object recognition technology model, which is an artificial intelligence technology, as a method for detecting the defects of expiration date printed on the product packaging. Using the Faster R-CNN (region convolution neural network) model, the color images, converted gray images, and converted binary images of the printed expiration date are trained and then tested, and each detection rates are compared. The detection performance of expiration date printed on the package by the proposed method showed the same detection performance as that of conventional vision-based inspection system.