• Journal of Digital Contents Society
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• v.17 no.5
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• pp.375-381
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• 2016

Recently, a foreground-background segmentation using codebook model has been researched actively. The codebook is created one for each pixel in the image. The codewords are vector-quantized representative values of same positional training samples from the input image sequences. The training is necessary for a long time in the most of codebook-based algorithms. In this paper, the initial codebook model is generated simply using median operation with several image frames. The initial codebook is updated to adapt the dynamic changes of backgrounds based on the frequencies of codewords that matched to input pixel during the detection process. We implemented the proposed algorithm in the environment of visual c++ with opencv 3.0, and tested to some of the public video sequences from PETS2009. The test sequences contain the various scenarios including quasi-periodic motion images, loitering objects in the local area for a short time, etc. The experimental results show that the proposed algorithm has good performance compared to the GMM algorithm and standard codebook algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.248-251
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• 2016

This thesis has discussed how to recognize and convert raised letters on tire to data and collect such data. Unlike the existing recognition system, the system presented by this thesis recognizes raised letters on tire through detecting letters after converting the Kinect camera image into image data in the preprocessing stage. After then, numbers and letters are analyzed through image improvement by use of binary images, noise filter, etc. In the recognition stage, letter distinction is used and raised letters on tire are recognized 100% through correction of errors by way of the correction algorithm for tire data recognition errors. In this paper it will be the development of a method of recognizing characters and the tire technology. Although there are many ways to the already recognized characters, Tire characters requires a technique different from the more general character recognition. For this reason and to develop additional technical methods and algorithms for character recognition.

• Journal of Digital Convergence
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• v.13 no.1
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• pp.249-255
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• 2015

Recent, there is increasing interest in AR(Augmented Reality). And various AR application programs using the latest Augmented Reality technology have been developed. In particular, researches about hair style simulator have been conducted for a long time. It can experience real-time a variety of hair styles to fit the taste of the customer. And some company has conducted the hair style simulator services. However, the most service products are the 2D hair style simulator did not apply the AR technology. Even though 3D hair style simulator has applied AR technology, a function of the NUI was lack. Therefore, in this paper have developed the 3D hair style simulator based on the core technology of AR like NUI as well as EHCI. 10 people was experienced the 3D hair style simulator. Finally, in this paper verifies the effectiveness of the 3D hair style simulator.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.94-102
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• 2015

Optical camera communication (OCC) is an extension of Visible Light Communication. Different from traditional visible light communication, optical camera communications is an almost no additional cost technology by taking the advantage of build-in camera in devices. It was became a candidate for communication protocol for IoT. Camera module can be easy attached to IoT device, because it is small and flexible. Furthermore almost smartphone equip one or two camera for both back and font side with high quality and resolution. It can be utilized for receiving the data from LED or positioning. Actually, OCC combines illumination and communication. It can supply communication for special areas or environment where do not allow Radio frequency such as hospital, airplane etc. There are many concept and experiment be proposed. In this paper we proposed utilizing Android smart-phone camera for receiver and introduce new approach in modulation scheme for LED at transmitter. It also show how Manchester coding can be used encode bits while at the same time being successfully decoded by Android smart-phone camera. We introduce new data frame format for easy decoded and can be achieve high bit rate. This format can be easy to adapt to performance limit of Android operator or embedded system.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.159-164
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• 2019

Detecting wildfire using only color in image information is a very difficult issue. This paper proposes an algorithm to detect forest fire area by analyzing color and motion of the area in the video including forest fire. The proposed algorithm removes the background region using the Gaussian Mixture based background segmentation algorithm, which does not depend on the lighting conditions. In addition, the RGB channel is changed to an HSV channel to extract flame candidates based on color. The extracted flame candidates judge that it is not a flame if the area moves while labeling and tracking. If the flame candidate areas extracted in this way are in the same position for more than 2 minutes, it is regarded as flame. Experimental results using the implemented algorithm confirmed the validity.

• KIEAE Journal
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• v.17 no.5
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• pp.95-100
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• 2017

Purpose: The purpose of this study is to investigate the prior art based on deep learning to objectively calculate the metabolic rate which is the subjective factor for the PMV optimum control and to make a plan for future research based on this study. Methods: For this purpose, the theoretical and technical review and applicability analysis were conducted through various documents and data both in domestic and foreign. Results: As a result of the prior art research, the machine learning model of artificial neural network and deep learning has been used in various fields such as speech recognition, scene recognition, and image restoration. As a representative case, OpenCV Background Subtraction is a technique to separate backgrounds from objects or people. PASCAL VOC and ILSVRC are surveyed as representative technologies that can recognize people, objects, and backgrounds. Based on the results of previous researches on deep learning based on metabolic rate for occupational metabolic rate, it was found out that basic technology applicable to occupational metabolic rate calculation technology to be developed in future researches. It is considered that the study on the development of the activity quantity calculation model with high accuracy will be done.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.152-155
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• 2019

클라우드가 대중화되어 많은 모바일 유저들이 자동 백업 기능을 사용하면서 민감한 개인정보가 포함된 사진들이 무분별하게 클라우드에 업로드 되고 있다. 개인정보를 포함한 클라우드가 악의적으로 해킹 될 시, 사진에 포함된 지문, 자동차 번호판, 카드 번호 등이 유출됨에 따라 대량의 개인정보가 유출될 가능성이 크다. 이에 따라 적절한 기준에 맞게 사진 속 개인 정보 유출을 막을 수 있는 기술의 필요성이 대두되고 있다. 현재의 클라우드 시스템의 문제를 해결하고자 본 연구는 모바일 기기에서 클라우드 서버로 사진을 백업하는 과정에서 영역 검출과 블러링의 과정을 제안하고 있다. 클라우드 업로드 과정에서 사진 속의 개인 정보를 검출한 뒤 이를 블러링하여 클라우드에 저장함으로써 악의적인 접근이 행해지더라도 개인정보의 유출을 방지할 수 있다. 머신러닝과 computer vision library등을 이용하여 이미지 내에 민감한 정보를 포함하고 있는 영역을 학습된 모델을 통해 검출한 뒤, OpenCV를 이용하여 블러링처리를 진행한다 사진 속에 포함될 수 있는 생체정보인 지문은 손 영역을 검출한 뒤, 해당 영역을 블러링을 하여 업로드하고 카드번호나 자동차 번호판이 포함된 사진은 영역을 블러링한 뒤, 암호화하여 업로드 된다. 후에 필요에 따라 본인인증을 거친 후 일정기간 열람을 허용하지만 사용되지 않을 경우 삭제되도록 한다. 개인정보 유출로 인한 피해가 꾸준히 증가하고 있는 지금, 사진 속의 개인 정보를 보호하는 기술은 안전한 통신과 더불어 클라우드의 사용을 더 편리하게 할 수 있을 것으로 기대된다.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.19 no.2
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• pp.161-176
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• 2021

In this study, the electrochemical behavior of Sm on the binary liquid Al-Ga cathode in the LiCl-KCl molten salt system is investigated. First, the co-reduction process of Sm(III)-Al(III), Sm(III)-Ga(III), and Sm(III)-Ga(III)-Al(III) on the W electrode (inert) were studied using cyclic voltammetry (CV), square-wave voltammetry (SWV) and open circuit potential (OCP) methods, respectively. It was identified that Sm(III) can be co-reduced with Al(III) or Ga(III) to form Al_zSm_y or Ga_xSm_y intermetallic compounds. Subsequently, the under-potential deposition of Sm(III) at the Al, Ga, and Al-Ga active cathode was performed to confirm the formation of Sm-based intermetallic compounds. The X-ray diffraction (XRD) and scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) analyses indicated that Ga₃Sm and Ga₆Sm intermetallic compounds were formed on the Mo grid electrode (inert) during the potentiostatic electrolysis in LiCl-KCl-SmCl₃-AlCl₃-GaCl₃ melt, while only Ga₆Sm intermetallic compound was generated on the Al-Ga alloy electrode during the galvanostatic electrolysis in LiCl-KCl-SmCl₃ melt. The electrolysis results revealed that the interaction between Sm and Ga was predominant in the Al-Ga alloy electrode, with Al only acting as an additive to lower the melting point.

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.19-27
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• 2021

In this paper, we propose a method for detecting characters in images and detecting facial regions, which consists of two tasks. First, we separate two different characters to detect the face position of the characters in the frame. For fast detection, we use You Only Look Once (YOLO), which finds faces in the image in real time, to extract the location of the face and mark them as object detection boxes. Second, we present three image processing methods to detect accurate face area based on object detection boxes. Each method uses HSV values extracted from the region estimated by the detection figure to detect the face region of the characters, and changes the size and shape of the detection figure to compare the accuracy of each method. Each face detection method is compared and analyzed with comparative data and image processing data for reliability verification. As a result, we achieved the highest accuracy of 87% when using the split rectangular method among circular, rectangular, and split rectangular methods.

• Journal of Practical Engineering Education
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• v.12 no.2
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• pp.309-319
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• 2020

Billiards is a fun and popular sport, but both route planning and cueing prevent beginners from becoming skillful. A beginner in billiards requires constant concentration and training to reach the right level, but without the right motivating factor, it is easy to lose interests. This study aims to induce interest in billiards and accelerate learning by utilizing billiard path prediction and visualization on a highly immersive augmented reality platform that combines a stereo camera and a VR headset. For implementation, the placement of billiard balls is recognized through the OpenCV image processing program, and physics simulation, path search, and visualization are performed in Unity Engine. As a result, accurate path prediction can be achieved. This made it possible for beginners to reduce the psychological burden of planning the path, focus only on accurate cueing, and gradually increase their billiard proficiency by getting used to the path suggested by the algorithm for a long time. We confirm that the proposed AR billiards is remarkably effective as a learning assistant tool.