• Journal of Digital Convergence
• /
• v.10 no.2
• /
• pp.237-242
• /
• 2012

This paper proposed image matching technique that find out the truth of the wild ginseng through smart phone when the common person discovered a plant like a wild ginseng. Also sharing a location and information by SNS, we can improve the probability of wild ginseng discovery. Image matching technique using OpenCV porting in android finds out the truth of the wild ginseng with comparing existing it. Thus we are able to compare and analysis them in our application program. For more verification, we added marking function of wild ginseng position for information sharing between users.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.10a
• /
• pp.538-539
• /
• 2018

This paper summarizes the implementation of lane recognition using OpenCV, one of the open source computer vision libraries. The Linux operating system Rasbian(r18.03.13) was installed on the ARM processor-based Raspberry Pi 3 board, and Raspberry Pi Camera was used for image processing. In order to realize the lane recognition, Canny Edge Detection and Hough Transform algorithm implemented in OpenCV library was used and RANSAC algorithm was used to prevent shaking of vanishing point and to detect only the desired straight line. In addtion, the DC motor and the Servo motor were controlled so that the vehicle would run according to the detected lane.

• Proceedings of the Korean Information Science Society Conference
• /
• 2007.10b
• /
• pp.55-60
• /
• 2007

소프트웨어가 전함에 따라 프로젝트의 규모가 커지게 되고, 참여 인원이 늘어나게 된다. 대규모의 프로젝트를 관리하는 것은 매우 복잡하고 어려운 작업이다. 버전관리 시스템은 이러한 대규모의 프로젝트를 관리하는데 있어 매우 유용한 도구로써 사용되고 있다. RSC, SCCS, 클리어케이스, CVS등 많은 버전관리 시스템이 있지만, 그 중 CVS는 대표적인 버전관리 시스템으로써 대부분의 오픈 소스 프로젝트에서 사용되고 있을 정도로 그 성능을 인정받고 있다. 본 연구에서는 버전관리 시스템의 가장 완성적인 형태라고도 불리는 CVS에 대한 특징을 연구하고 CVS가 가지는 장 단점을 살펴보고 CVS의 성능을 개선시킬 수 있는 자동화된 버전관리 시스템을 제안한다.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.6
• /
• pp.1193-1198
• /
• 2022

As unmanned processing systems emerged socially due to the rapid development of modern society, a face recognition attendance management system using Raspberry Pi 4 was studied and conceived to automatically analyze and process images and produce meaningful results using OpenCV. Based on Raspberry Pi 4, the software is designed with Python 3 and consists of technologies such as OpenCV, Haarcascade, Kakao API, and Google Drive, which are open sources, and can communicate with users in real time through Kakao API for face registration and face recognition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.10a
• /
• pp.541-544
• /
• 2012

In technology advances, The field of military and security surveillance system for a wide range of interest is required. Surveillance system offers a variety of services by the software that work with a remote access server. This paper shows the results of the implementation using three platforms as Mjpg-streamer for server, Arduino-multiwii for control system, OpenNI and OpenCV for image processing.

• Journal of the Korea Institute of Building Construction
• /
• v.24 no.1
• /
• pp.133-144
• /
• 2024

The OpenCV-based length measurement algorithm is anticipated to be effective for length measurement inspection tasks, providing objective inspection outcomes. Nonetheless, there is a notable gap in research regarding the influence of various checkerboard types and capturing conditions on the algorithm's accuracy in real-world construction settings. Consequently, this study proposes a methodology employing an OpenCV-based length measurement algorithm and checkerboard for digital construction inspection tasks. The findings suggest that using a checkerboard with square sizes of A4 or larger, and 50mm or larger, is optimal for capturing distances and angles within 4m and 90°, respectively, when deploying the algorithm. These insights are anticipated to provide practical guidelines for professionals conducting digital-based length measurement inspections.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.1
• /
• pp.93-100
• /
• 2020

In this paper, we implemented a smart mirror that helps users to measure the results before the procedure by reflecting various hairstyles on the head. When the camera is used to capture a face in real time and recognize the face, the stored hair image is uploaded to provide a virtual image. In addition, the high production cost, which is a problem of the existing smart mirrors, was reduced by using Raspberry Pi, Open CV, and half mirror film, and various functions were implemented through touch control. It is also designed to provide information such as weather, calendar and time.

• Journal of Digital Convergence
• /
• v.19 no.2
• /
• pp.245-251
• /
• 2021

As the trend of steadily increasing the number of single or double household, there is a growing demand to see who is the outsider visiting the home during the free time. Various models of face recognition technology have been proposed through many studies, and Harr Cascade of OpenCV and Hog of Dlib are representative open source models. Among the two modes, Dlib's Hog has strengths in front of the indoor and at a limited distance, which is the focus of this study. In this paper, a face recognition visitor access system based on Dlib was designed and implemented. The whole system consists of a front module, a server module, and a mobile module, and in detail, it includes face registration, face recognition, real-time visitor verification and remote control, and video storage functions. The Precision, Specificity, and Accuracy according to the change of the distance threshold value were calculated using the error matrix with the photos published on the Internet, and compared with the results of previous studies. As a result of the experiment, it was confirmed that the implemented system was operating normally, and the result was confirmed to be similar to that reported by Dlib.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2019.10a
• /
• pp.615-618
• /
• 2019

이 모듈은 오픈소스인 Tesseract OCR 및 Open CV 라이브러리와 Raspberry Pi를 사용하여 저렴한 비용으로 구현합니다. 컴팩트한 사이즈로 사람이 직접 들고 움직이면서도 사용이 가능하며 사용자의 니즈에 따라서 한 곳에 위치하여도 사용 가능합니다. Open CV 라이브러리를 사용하여 이미지 이진화, 노이즈 필터링 후에 흑백 이미지를 만들고 윤곽선 검출 알고리즘을 통해서 번호판 영역을 추출하여 Tesseract OCR 엔진을 사용해서 차량 번호판이 추출된 이미지에서 차량 번호를 인식 합니다. 인식된 번호는 Tkinter 와 Python, 데이터베이스를 활용하여 구현된 GUI프로그램을 통해서 유료주차장(선불, 후불) 또는 아파트에서 사용할 수 있는 주차장 관리 서비스를 함께 제공합니다.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.14 no.1
• /
• pp.169-177
• /
• 2014

It is essential to support the image and video analysis technology such as motion detection since the DVR and NVR storage were adopted in the real time visual surveillance system. Especially the network camera would be popular as a video input device. The traditional CCTV that supports analog video data get be replaced by the network camera. In this paper, we present the design and implementation of video surveillance system that provides the real time motion detection by the video storage server. The mobile application also has been implemented in order to provides the retrieval functionality of image analysis results. We develop the video analysis server with open source library OpenCV and implement the daemon process for video input processing and real-time image analysis in our video surveillance system.