• Title/Summary/Keyword: open CV

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Non-pneumatic Tire Design System based on Generative Adversarial Networks (적대적 생성 신경망 기반 비공기압 타이어 디자인 시스템)

  • JuYong Seong;Hyunjun Lee;Sungchul Lee
    • Journal of Platform Technology
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    • v.11 no.6
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    • pp.34-46
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    • 2023
  • The design of non-pneumatic tires, which are created by filling the space between the wheel and the tread with elastomeric compounds or polygonal spokes, has become an important research topic in the automotive and aerospace industries. In this study, a system was designed for the design of non-pneumatic tires through the implementation of a generative adversarial network. We specifically examined factors that could impact the design, including the type of non-pneumatic tire, its intended usage environment, manufacturing techniques, distinctions from pneumatic tires, and how spoke design affects load distribution. Using OpenCV, various shapes and spoke configurations were generated as images, and a GAN model was trained on the projected GANs to generate shapes and spokes for non-pneumatic tire designs. The designed non-pneumatic tires were labeled as available or not, and a Vision Transformer image classification AI model was trained on these labels for classification purposes. Evaluation of the classification model show convergence to a near-zero loss and a 99% accuracy rate confirming the generation of non-pneumatic tire designs.

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Design of 3D GUI Simulator for Integrated BTT Missile System (고기동 BTT 미사일 시스템의 통합 시뮬레이션을 위한 GUI 구현)

  • Park, Se-Beom;Yeom, Joon-Hyung;Ha, In-Joong
    • Proceedings of the KIEE Conference
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    • 2009.07a
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    • pp.1790_1791
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    • 2009
  • OpenCV을 사용하여 MFC/OpenGL 환경의 BTT 미사일을 설계하였다. 시뮬레이션을 수행 하는 동안의 이미지에서 표적의 특징점(Feature point)를 추출해 호모그래피 행렬(Homography Matrix)을 계산하여 이로부터 표적의 위치, 속도, 자세 정보등을 추정하도록 하였다. 그리고 미사일 동역학, 자동 조종 장치 역시 C로 구현하여 통합 시뮬레이션 환경을 구축하였다.

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Implementation of Hand-Gesture Interface to manipulate a 3D Object of Augmented Reality (증강현실의 3D 객체 조작을 위한 핸드-제스쳐 인터페이스 구현)

  • Jang, Myeong-Soo;Lee, Woo-Beom
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.16 no.4
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    • pp.117-123
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    • 2016
  • A hand-gesture interface to manipulate a 3D object of augmented reality is implemented by recognizing the user hand-gesture in this paper. Proposed method extracts the hand region from real image, and creates augmented object by hand marker recognized user hand-gesture. Also, 3D object manipulation corresponding to user hand-gesture is performed by analyzing a hand region ratio, a numbet of finger and a variation ratio of hand region center. In order to evaluate the performance of the our proposed method, after making a 3D object by using the OpenGL library, all processing tasks are implemented by using the Intel OpenCV library and C++ language. As a result, the proposed method showed the average 90% recognition ratio by the user command-modes successfully.

Fast Video Data Encryption for Swarm UAVs Using Hybrid Crypto-system (하이브리드 암호시스템을 이용한 군집 영상의 고속 암호화)

  • Cho, Seong-Won;Kim, Jun-Hyeong;Chae, Yeo-Gyeong;Joung, Yu-Min;Park, Tae-Kyou
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.46 no.7
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    • pp.602-609
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    • 2018
  • This paper proposes the hybrid crypto-system for fast video data encryption of UAV(Unmanned Aerial Vehicle) under the LTE(Long-Term Evolution) wireless communication environment. This hybrid crypto-system is consisted of ECC(Elliptic Curve Cryptography) public key algorithm and LEA(Light-weight Encryption Algorithm) symmetric key algorithm. ECC is a faster public key algorithm with the same security strength than RSA(Rivest Shamir Adleman), and Korean standard LEA with the same key size is also a faster symmetric key algorithm than AES(Advances Encryption Standard). We have implemented this hybrid crypto-system using OpenSSL, OpenCV and Socket programs under the Swarm 8-UAV. We have shown the efficient adaptability of this hybrid crypto-system for the real-time swarm UAV through the experiments under the LTE communication environment.

Video Stabilization Algorithm of Shaking image using Deep Learning (딥러닝을 활용한 흔들림 영상 안정화 알고리즘)

  • Lee, Kyung Min;Lin, Chi Ho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.1
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    • pp.145-152
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    • 2019
  • In this paper, we proposed a shaking image stabilization algorithm using deep learning. The proposed algorithm utilizes deep learning, unlike some 2D, 2.5D and 3D based stabilization techniques. The proposed algorithm is an algorithm that extracts and compares features of shaky images through CNN network structure and LSTM network structure, and transforms images in reverse order of movement size and direction of feature points through the difference of feature point between previous frame and current frame. The algorithm for stabilizing the shake is implemented by using CNN network and LSTM structure using Tensorflow for feature extraction and comparison of each frame. Image stabilization is implemented by using OpenCV open source. Experimental results show that the proposed algorithm can be used to stabilize the camera shake stability in the up, down, left, and right shaking images.

Segmentation of underwater images using morphology for deep learning (딥러닝을 위한 모폴로지를 이용한 수중 영상의 세그먼테이션)

  • Ji-Eun Lee;Chul-Won Lee;Seok-Joon Park;Jea-Beom Shin;Hyun-Gi Jung
    • The Journal of the Acoustical Society of Korea
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    • v.42 no.4
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    • pp.370-376
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    • 2023
  • In the underwater image, it is not clear to distinguish the shape of the target due to underwater noise and low resolution. In addition, as an input of deep learning, underwater images require pre-processing and segmentation must be preceded. Even after pre-processing, the target is not clear, and the performance of detection and identification by deep learning may not be high. Therefore, it is necessary to distinguish and clarify the target. In this study, the importance of target shadows is confirmed in underwater images, object detection and target area acquisition by shadows, and data containing only the shape of targets and shadows without underwater background are generated. We present the process of converting the shadow image into a 3-mode image in which the target is white, the shadow is black, and the background is gray. Through this, it is possible to provide an image that is clearly pre-processed and easily discriminated as an input of deep learning. In addition, if the image processing code using Open Source Computer Vision (OpenCV)Library was used for processing, the processing speed was also suitable for real-time processing.

A Design and Implementation of Generative AI-based Advertising Image Production Service Application

  • Chang Hee Ok;Hyun Sung Lee;Min Soo Jeong;Yu Jin Jeong;Ji An Choi;Young-Bok Cho;Won Joo Lee
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.5
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    • pp.31-38
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    • 2024
  • In this paper, we propose an ASAP(AI-driven Service for Advertisement Production) application that provides a generative AI-based automatic advertising image production service. This application utilizes GPT-3.5 Turbo Instruct to generate suitable background mood and promotional copy based on user-entered keywords. It utilizes OpenAI's DALL·E 3 model and Stability AI's SDXL model to generate background images and text images based on these inputs. Furthermore, OCR technology is employed to improve the accuracy of text images, and all generated outputs are synthesized to create the final advertisement. Additionally, using the PILLOW and OpenCV libraries, text boxes are implemented to insert details such as phone numbers and business hours at the edges of promotional materials. This application offers small business owners who face difficulties in advertising production a simple and cost-effective solution.

Influence of PE Film House culture with Non Heating on Growth and Yield of Forage Rape (무가온 Vinyl House 재배가 사초유채의 생산특성과 수량에 미치는 영향)

  • 안계수;권병선;정동희;김상곤
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.16 no.3
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    • pp.215-218
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    • 1996
  • This study examines the possibility of early production of forage rape (cv. Akela and Velox) in the period of wintering. Bolting date was Feb. 2 to Feb. 9 in PE film house culture by non-heating and Mar. 3 to Mar. 12 in open field culture. And flowering date was Feb. 24 to Mar. 3 in PE film house culture by non-heating, so it was 30~50 days faster than the open field culture of Apr. 17 to Apr. 22. Fresh matter yield was 8, 356~4, 887 kg/10a in PE film house culture by non-heating, so it was 1, 431~1, 603 kg/10a yield increase than in the open field culture of 7, 253~7, 456 kg/10a Dry matter yield was 953~963 kg/10a in PE film house culture by non-heating, so it was 71~284 kg/10a yield increase than in the open field culture of 669~892 kg/10a.

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Performance Analysis of Feature Detection Methods for Topology-Based Feature Description (토폴로지 기반 특징 기술을 위한 특징 검출 방법의 성능 분석)

  • Park, Han-Hoon;Moon, Kwang-Seok
    • Journal of the Institute of Convergence Signal Processing
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    • v.16 no.2
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    • pp.44-49
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    • 2015
  • When the scene has less texture or when camera pose largely changes, the existing texture-based feature tracking methods are not reliable. Topology-based feature description methods, which use the geometric relationship between features such as LLAH, is a good alternative. However, they require feature detection methods with high performance. As a basic study on developing an effective feature detection method for topology-based feature description, this paper aims at examining their applicability to topology-based feature description by analyzing the repeatability of several feature detection methods that are included in the OpenCV library. Experimental results show that FAST outperforms the others.

An Intelligent Wireless Camera Surveillance System with Motion sensor and Remote Control (무선조종과 모션 센서를 이용한 지능형 무선감시카메라 구현)

  • Lee, Young-Woong;Kim, Jong-Nam
    • Proceedings of the Korea Contents Association Conference
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    • 2009.05a
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    • pp.672-676
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    • 2009
  • Recently, intelligent surveillance camera systems are needed popularly. However, current researches are focussed on improvement of a single module rather than implementation of an integrated system. In this paper, we implemented a wireless surveillance camera system which is composed of face detection, and using motion sensor. In our implementation, we used a camera module from SHARP, a pair of wireless video transmission module from ECOM, a pair of ZigBee RF wireless transmission module from ROBOBLOCK, and a motion sensor module (AMN14111) from PANASONIC. We used OpenCV library for face dection and MFC for implement software. We identified real-time operations of face detection, PTT control, and motion sensor detecton. Thus, the implemented system will be useful for the applications of remote control, human detection, and using motion sensor.

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