• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.327-329
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• 2019

In this paper, we propose an automatic attendance management system for classrooms using OpenCV and machine learning technology. When a face photograph is input at the entrance of the classroom using a general purpose camera for PC, the attendance is checked by comparing the similarity of the face of the already stored student. In this study, the prototype was implemented using the machine learning library dlib, and about 10% of the students had a recognition rate of about 70%.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.87-96
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• 2018

In this paper, we propose a method to determine whether there is a defect by using the similarity between ROIs (Region of Interest) of the standard image and ROIs of the image which is corrected in position and rotation after capturing the vehicle headlight. The degree of similarity is determined by the template matching based on the histogram of image, which is a some modification of the method provided by OpenCV where template matching is performed on the raw image not the histogram. The proposed method is compared with the basic method of OpenCV for performance analysis. As a result of the analysis, it was found that the proposed method showed better performance than the OpenCV method, showing the accuracy close to 100%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.700-702
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• 2018

In this abstract, introduces a system that enables communication by tracking the pupils of Lou Gehrig's disease patients who are unable to move their bodies. Face and eye pupil tracking perform using OpenCV, and eye movement recognition and character selection by eye movement is obtained using Python. In this paper, you will use the webcams, track your eyes, determine eye movements based on the coordinates of your pupils, and print characters that meet your preferences. It can easily output text messages using Bluetooth.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.379-380
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• 2018

Previoisly presented "Implementation to pupil motion recognition system using convolution neural network".is improved. Using OpenCV, face and eye areas are detected, and then configure the neural network using Numpy. This pupil motion recognition system is based on the Numpy for configuring and calculating the neural network. This system is implemented on DE1-SOC.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1193-1198
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• 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 Korea Contents Association Conference
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• 2009.05a
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• pp.79-82
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• 2009

In this paper, we propose new image processing method to detect fire image. At captured image from camera, we using OpenCV library to implement various image processing techniques such like differential image, binarization image, contour extraction, remove noise(morphology open, close), pixel calculation, flickering extraction, etc.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.356-358
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• 2012

본 논문에서는 OpenCV를 이용한 영상처리 작업환경에서 영상처리 결과에 따라 마커를 기반으로 한 복잡한 형태의 3D 애니메이션 객체를 띄우기 위해 사용되는 증강현실 라이브러리(ARToolkit, OpenVRML)를 함께 사용하는 시스템을 제시하였다. OpenCV 라이브러리와 증강현실 라이브러리는 카메라로부터 이미지를 얻어오기 위한 함수 및 가져온 이미지 타입이 다르고 각각의 라이브러리에 맞게 이미지를 처리하기 위한 설정 및 최종적으로 디스플레이 하기 위한 일련의 과정에 있어서 호출되는 모듈들이 상이하였다. 또한 ARToolkit내에서도 보다 복잡한 3D객체의 렌더링을 수월하게 하기 위한 OpenVRML 기반 렌더링과 개발자가 원하는 렌더링을 손쉽게 수행할 수 있는 OpenGL 기반 렌더링과의 병렬적인 연동에 있어서 두 라이브러리를 사용하는 프로젝트의 카메라 및 렌더링 설정과 렌더링 처리 절차에 차이가 있어 두 프로젝트의 기능별 모듈을 하나로 통합하였다. 그리고 영상처리 라이브러리의 이미지 처리에 대한 모듈을 전체 시스템의 처리 순서에 맞게 알맞은 함수들로 배정하여 이 함수 내에서 추후 개발자가 개발한 시스템에 맞게 직접 편집하여 활용할 수 있도록 하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.69-75
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• 2020

This paper introduces the parking guide service developed to address the inconvenience of parking in areas where demand for parking spaces is high, such as busy streets and tourist attractions. Due to difficulties in measuring and developing the actual parking lot while driving the car, we created a temporary parking lot and created Arduino RC Car to replace the actual car. Video processing based on Open CV allows users to identify the entire parking lot, parking space, and completed parking space, and track moving cars, and this information has been developed to enable users to see through the application. The application allows the user to book the desired parking space and introduce a way-finding algorithm to guide them through the optimal path to the selected parking compartment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.696-699
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• 2018

This paper introduces a system that enables pupillary tracing and communication with patients with amyotrophic lateral sclerosis (ALS) who can not move free. Face and pupil are tracked using OpenCV, and eye movements are detected using DE1-SoC board. We use the webcam, track the pupil, identify the pupil's movement according to the pupil coordinate value, and select the character according to the user's intention. We propose a system that can use relatively low development cost and FPGA can be reusable, and can select a text easily to mobile phone by using Bluetooth.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.2
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• pp.267-274
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• 2015

In this paper the optimal structure of a neural network based on OpenCV for a golf ball recognition and the intensity of ROI(Region Of Interest) are calculated. The system is composed of preprocess, image processing and machine learning, and a learning model is obtained by multi-layer perceptron using the inputs of 7 Hu's invariant moments, box ration extracted by vertical and horizontal length or ${\pi}$ calculated by area of ROI. Simulation results show that optimal numbers of hidden layer and the node of neuron are selected to 2 and 9 respectively considering the recognition rate and running time, and optimal intensity of ROI is selected to 200.