• Journal of the Korea Convergence Society
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• v.7 no.4
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• pp.173-180
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• 2016

OpenCV is a programming language used in digital image processing and computer vision. In this study, look at media arts made using OpenCV programming language and find out about the utilization possibilities. To this end, the first, look at OpenCV functions that are frequently used in media art, the examples of utilizing the functions. The second, discuss media arts using OpenCV. focused on the OpenCV functions, programming language for an production of media art. The third, analyze features of media arts using OpenCV, mainly focused on the functions and programming languages. The study may provide guidance to the artists to produce a media art using the OpenCV or programming language.

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.75-78
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• 2022

Deep Neural Networks (DNN) has become an essential data processing architecture for the implementation of multiple computer vision tasks. Recently, DNN-based algorithms achieve much higher recognition accuracy than traditional algorithms based on shallow learning. However, training and inference DNNs require huge computational capabilities than daily usage purposes of computers. Moreover, with increased size and depth of DNNs, CPUs may be unsatisfactory since they use serial processing by default. GPUs are the solution that come up with greater speed compared to CPUs because of their Parallel Processing/Computation nature. In this paper, we analyze the inference time complexity of DNNs using well-known computer vision library, OpenCV. We measure and analyze inference time complexity for three cases, CPU, GPU-Float32, and GPU-Float16.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.2
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• pp.211-218
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• 2021

Construction sites have various risk factors. There are various approaches to reduce safety accidents, but they have limitations to some extent. By utilizing the wireless communication technology of IT and the rapidly developing image processing technology, it will be possible to reduce accidents at the construction site if risk factors are identified and actively responded to. Therefore, in this study, a system that can detect risk factors of construction sites in advance is constructed, and a system is proposed to discover and respond to risk factors of construction sites using OpenCV for the purpose of real-time computer vision.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.161-170
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• 2024

With the technological advances, the humans have made so much progress in the ease of living and now incorporating the use of sight, motion, sound, speech etc. for various application and software controls. In this paper, we have explored the project in which gestures plays a very significant role in the project. The topic of gesture control which has been researched a lot and is just getting evolved every day. We see the usage of computer vision in this project. The main objective that we achieved in this project is controlling the computer settings with hand gestures using computer vision. In this project we are creating a module which acts a volume controlling program in which we use hand gestures to control the computer system volume. We have included the use of OpenCV. This module is used in the implementation of hand gestures in computer controls. The module in execution uses the web camera of the computer to record the images or videos and then processes them to find the needed information and then based on the input, performs the action on the volume settings if that computer. The program has the functionality of increasing and decreasing the volume of the computer. The setup needed for the program execution is a web camera to record the input images and videos which will be given by the user. The program will perform gesture recognition with the help of OpenCV and python and its libraries and them it will recognize or identify the specified human gestures and use them to perform or carry out the changes in the device setting. The objective is to adjust the volume of a computer device without the need for physical interaction using a mouse or keyboard. OpenCV, a widely utilized tool for image processing and computer vision applications in this domain, enjoys extensive popularity. The OpenCV community consists of over 47,000 individuals, and as of a survey conducted in 2020, the estimated number of downloads exceeds 18 million.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.763-764
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• 2008

Sensing is an important part of a smart home system. Vision sensors are a type of passive systems, which are not sensitive to noise. In this paper, we implement a prototype for stereo vision systems using OpenCV. It is an open source library for computer vision developed by Intel corporation. The prototype will by used for comparing performance among various stereo algorithms and for developing a stereo vision smart camera.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.61-64
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• 2013

본 논문에서는 모바일 기반 OpenCV 라이브러리를 이용한 마커리스 객체 인석 성능 향상을 위한 소프트웨어적인 관점의 방법을 제안한다. 기존의 마커리스 기반 알고리즘을 이용하여 테스트를 수행한 후 성능에 저하를 발생시키는 요인들을 분석하고 그에 따른 상황별 적절한 해결책을 제시한다. 이에 따라 크게 프로그램 코드 개선, 마커리스 기반 알고리즘 코드 개선, 센서를 활용한 성능 향상을 도모한다. 프로그램 코드 개선은 테스트 결과를 분석 한 후 수행시간이 가장 많이 소요되는 함수를 최적화하고 또한 최적의 특징점의 수를 제한한다. 마커리스 기반 알고리즘 코드 개선은 병렬 처리가 제공되는 모바일에 한하여 병렬처리기법으로 코드를 수정한다. 마지막 센서를 활용한 성능향상은 실시간 작업 처리 단위를 묶음으로 처리하였을 때 발생하는 품질의 저하를 보정하는 역할을 수행한다. 본 논문에서는 이러한 마커리스 객체 인식 성능 향상 방법을 소프트웨어적인 관점에서 제안하고 이에 대한 결과 모바일 기반 실시간 증강현실 서비스를 위한 성능 향상 면에서 효과적이다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.538-539
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• 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 Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.393-394
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• 2018

In this paper, the new system which improve the previously reported "Implementation to human-computer interface system with motion tracking using OpenCV and FPGA" is introduced and in this system, a character selection system for the physically uncomfortable patients is proposed. Using OpenCV, the eye area is detected, the pupil position is determined, and then the results are sent to the FPGA, and the character is selected finally. The method to minimize the pupil movement of the patient is used to output the character according to the user's intention. Using OpenCV, various computer vision algorithms can be easily applied, and using programmable FPGA, a pupil motion recognition and character selection system are implemented with a low cost.

• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.17-23
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• 2016

NUI is a motion interface. It uses the body of the user without the use of HID device such as a mouse and keyboard to control the device. In this paper, we use a Pi Camera and sensors connected to it with small embedded board Raspberry Pi. We are using the OpenCV algorithms optimized for image recognition and computer vision compared with traditional HID equipment and to implement a more human-friendly and intuitive interface NUI devices. comparison operation detects motion, it proposed a more advanced motion sensors and recognition systems fused connected to the Raspberry Pi.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.111-112
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• 2007

본 논문에서는 멀티프로세서 기반의 고속 영상처리 알고리즘 개발방법에 대해 소개한다. 영상획득 방식의 발전과 더불어 고해상도 영상의 획득이 가능해지고 영상이 컬러화가 되면서 많은 영상처리 응용분야에서 알고리즘 고속화를 필요로 하고 있다. 이러한 수요를 만족시키기 위해서는 최근에 출시되고 있는 멀티프로세서를 최대한 활용할 수 있는 알고리즘 개발이 최우선이다. 본 논문에서는 OpenMP, MIL(Matrox Image Library), OpenCV, IPP(Integrated Performance Primitives), SSE (Streaming SIMD (Single Instruction Multiple Data) Extensions)등 병렬처리와 고속 영상처리 라이브러리를 이용한 알고리즘 개발방법에 대해 소개하고, 각 개발방법에 따른 알고리즘 성능을 분석 및 평가하였다. 실험결과로부터 SSE와 IPP, MIL(Thread)을 이용하여 Mean, Dilation, Erosion, Open, Closing, Sobel등 알고리즘을 구현하여 $4057{\times}4048$크기의 영상에 적용하였을 때 $7{\sim}35msec$의 좋은 성능을 나타내어 기타 방식보다 우수함을 알 수 있었다.