• 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 Digital Convergence
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• v.12 no.6
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• pp.231-236
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• 2014

In this paper, we propose a processing speed improvement by adding a parallel processing based on device(graphic card) into a road region extraction by host(PC) based serial processing. The OpenCV CUDA supports the many functions of parallel processing method by interworking a conventional OpenCV with CUDA. Also, when interworking the OpenCV and CUDA, OpenCV functions completed a configuration are optimized the User's device(Graphic Card) specifications. Thus, OpenCV CUDA usage provides an algorithm verification and easiness of simulation result deduction. The proposed method is verified that the proposed method has a about 3.09 times faster processing speed than a conventional method by using OpenCV CUDA and graphic card of NVIDIA GeForce GTX 560 Ti model through experimentation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.303-304
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• 2021

It is an important issue to detect automatically whether a mask is worn or not for corona prevention. It is known that mask wearing detection can be solved by learning the face data set. However, the search for whether a person is wearing a mask can be detected in a simpler way using OpenCV. In this paper, we describe that it is possible to easily detect whether a single person is wearing a mask or not with a general PC camera using OpenCV learning data results and simple OpenCV functions. Through experiments, the proposed method was shown to be effective.

• 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 Korea Information Processing Society Conference
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• 2011.11a
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• pp.18-20
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• 2011

최근 컴퓨터 비전의 활용 영역이 증가함에 따라 컴퓨터 비전의 대표적인 라이브러리인 openCV의 사용 또한 증가하는 추세이다. openCV 에는 컴퓨터 비전 알고리즘의 특성상 massive 한 연산을 수행해야 하는 부분이 상당수 존재한다. 본 논문은 이러한 연산량의 부담을 줄임으로써 openCV 의 성능 향상을 위한 아키텍처를 연구한다. openCV 의 massive 한 연산은 라이브러리 함수에 있는 내부 반복문에서 발생하기 때문에, 본 논문은 반복문의 특성을 분석하고 이를 가속할 수 있는 아키텍처가 무엇인지 연구한다. 결론적으로 반복문의 각 iteration 이 독립적일 경우에는 SIMD (Single Instruction Multiple Data)와 SIMT (Single Instruction Multiple Thread)이 적합하며 반복문의 각 iteration 이 의존적일 경우에는 MIMD (Multiple Instruction Multiple Data)를 바탕으로 하는 파이프라인 아키텍처가 적합하다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.637-639
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• 2021

As autonomous driving research is actively progressing, lane detection is an essential technology in ADAS (Advanced Driver Assistance System) to locate a vehicle and maintain a route. Lane detection is detected using an image processing algorithm such as Hough transform and RANSAC (Random Sample Consensus). This paper implements a linear shape detection algorithm using OpenCV on Raspberry Pi 3 B+. Thresholds were set through OpenCV Gaussian blur structure and Canny edge detection, and lane recognition was successful through linear detection algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.834-835
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• 2016

In recent years, advances in technology, IT is rapidly growing. Accordingly, real time image processing and multiple platforms, providing compatibility with OpenCV for image processing technology research on actively in progress. At present, different, comparing the images to determine the similarity is low, the system will match the rate of people using the analogue figures to determine the system is for the most part. In this paper, Template Matching of OpenCV and Feature Matching utilizing different images to determine the similarity between digital values for the system. A comparison of the features of a specific point on the screen the image to extract the same feature in a different size, you can compare the features of the target image recognized as compared to three historic castle in comparison, verification. This is the voice and image recognition and analysis, check the matching rate readings than in Zhengzhou treatment techniques are available. The future of forensic and other image processing technologies for OpenCV studies will be needed to feed.

• 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.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.298-304
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• 2021

Currently, to prevent the spread of COVID-19 virus infection, gathering of more than 5 people in the same space is prohibited. The purpose of this paper is to measure the distance between objects using the Yolov5 model for processing real-time images with OpenCV in order to restrict the distance between several people in the same space. Also, Utilize Euclidean distance calculation method in DeepSORT and OpenCV to minimize occlusion. In this paper, to detect the distance between people, using the open-source COCO dataset is used for learning. The technique used here is using the YoloV5 model to measure the distance, utilizing DeepSORT and Euclidean techniques to minimize occlusion, and the method of expressing through visualization with OpenCV to measure the distance between objects is used. Because of this paper, the proposed distance measurement method showed good results for an image with perspective taken from a higher position than the object in order to calculate the distance between objects by calculating the y-axis of the image.

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