• International journal of advanced smart convergence
• /
• 제12권4호
• /
• pp.182-189
• /
• 2023

A recently research, object detection and segmentation have emerged as crucial technologies widely utilized in various fields such as autonomous driving systems, surveillance and image editing. This paper proposes a program that utilizes the QT framework to perform real-time object detection and precise instance segmentation by integrating YOLO(You Only Look Once) and Mask R CNN. This system provides users with a diverse image editing environment, offering features such as selecting specific modes, drawing masks, inspecting detailed image information and employing various image processing techniques, including those based on deep learning. The program advantage the efficiency of YOLO to enable fast and accurate object detection, providing information about bounding boxes. Additionally, it performs precise segmentation using the functionalities of Mask R CNN, allowing users to accurately distinguish and edit objects within images. The QT interface ensures an intuitive and user-friendly environment for program control and enhancing accessibility. Through experiments and evaluations, our proposed system has been demonstrated to be effective in various scenarios. This program provides convenience and powerful image processing and editing capabilities to both beginners and experts, smoothly integrating computer vision technology. This paper contributes to the growth of the computer vision application field and showing the potential to integrate various image processing algorithms on a user-friendly platform

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제2권1호
• /
• pp.89-93
• /
• 2002

This paper introduces a vision-based on-line fabric inspection methodology of woven textile fabrics. Current procedure for determination of fabric defects in the textile industry is performed by human in the off-line stage. The advantage of the on-line inspection system is not only defect detection and identification, but also 벼ality improvement by a feedback control loop to adjust set-points. The proposed inspection system consists of hardware and software components. The hardware components consist of CCD array cameras, a frame grabber and appropriate illumination. The software routines capitalize upon vertical and horizontal scanning algorithms characteristic of a particular deflect. The signal to noise ratio (SNR) calculation based on the results of the wavelet transform is performed to measure any deflects. The defect declaration is carried out employing SNR and scanning methods. Test results from different types of defect and different style of fabric demonstrate the effectiveness of the proposed inspection system.

• 한국ITS학회 논문지
• /
• 제22권6호
• /
• pp.114-123
• /
• 2023

컴퓨터 비전(Computer Vision: CV) 기술 발전으로 폐쇄회로 TV(Closed-Circuit television: CCTV)와 같은 영상 센서로 돌발상황을 검지하고 있다. 그러나 현재 이러한 기술은 대부분 고정식 영상 센서를 기반으로 한다. 따라서 고정식 장비의 영상 범위가 닿지 않는 음영지역의 돌발상황 검지에는 한계가 존재해왔다. 최근 엣지 컴퓨팅(Edge-computing) 기술의 발전으로 이동식 영상정보의 실시간 분석이 가능해졌다. 본 연구는 차량 내 설치된 이동식 영상 센서(dashboard camera 혹은 dash cam)에 컴퓨터 비전 기술을 도입하여 고속도로에서 실시간으로 돌발상황 검지 가능성에 대해 평가하는 것이 목적이다. 이를 위해 한국도로공사 순찰차량에 장착된 dash cam에서 수집된 4,388건의 스틸 프레임 데이터 기반으로 학습데이터를 구축하였으며, YOLO(You Only Look Once) 알고리즘을 활용하여 분석하였다. 분석 결과 객체 모두 예측 정밀도가 70% 이상으로 나타났고, 교통사고는 약 85%의 정밀도를 보였다. 또한 mAP(mean Average Precision)의 경우 0.769로 나타났고, 객체별 AP(Average Precision)를 보면 교통사고가 0.904로 가장 높게 나타났고, 낙하물이 0.629로 가장 낮게 나타났다.

• 한국농업기계학회:학술대회논문집
• /
• 한국농업기계학회 1996년도 International Conference on Agricultural Machinery Engineering Proceedings
• /
• pp.802-811
• /
• 1996

Farmers need alternatives for weed control due to the desire to reduce chemicals used in farming. However, conventional mechanical cultivation cannot selectively remove weeds located in the seedline between crop plants and there are no selective heribicides for some crop/weed situations. Since hand labor is costly , an automated weed control system could be feasible. A robotic weed control system can also reduce or eliminate the need for chemicals. Currently no such system exists for removing weeds located in the seedline between crop plants. The goal of this project is to build a real-time , machine vision weed control system that can detect crop and weed locations. remove weeds and thin crop plants. In order to accomplish this objective , a real-time robotic system was developed to identify and locate outdoor plants using machine vision technology, pattern recognition techniques, knowledge-based decision theory, and robotics. The prototype weed control system is composed f a real-time computer vision system, a uniform illumination device, and a precision chemical application system. The prototype system is mounted on the UC Davis Robotic Cultivator , which finds the center of the seedline of crop plants. Field tests showed that the robotic spraying system correctly targeted simulated weeds (metal coins of 2.54 cm diameter) with an average error of 0.78 cm and the standard deviation of 0.62cm.

• 디자인학연구
• /
• 제20권3호
• /
• pp.257-268
• /
• 2007

인간 대 컴퓨터 인터페이스의 발전은 기술의 발전에 크게 의존되어 왔다. 그러나 인위적 환경을 통한 커뮤니케이션 방법인 키보드, 마우스나 OMR 등의 비직관적 인터페이스를 넘어선 직관적 인터페이스의 연구가 활발히 진행되고 있다. 이와 더불어 일반 가정에서도 대형화면 TV의 급속한 보급과 디지털환경을 통한 다양한 서비스의 제공이 이뤄지고 있다. 이러한 인터페이스와 TV환경의 변화는 인간 대 TV의 인터페이스에 획기적 변화를 요구하게 되었다. 기존의 인터페이스에서 동작인식을 기반으로 하는 인터페이스로의 전환은 보다 직관적인 인터페이스로서 제시될 수 있을 것이다. 본 연구에서는 지시동작인식이론과 디지털 TV 인터페이스 분석에 대한 이론을 바탕으로, 이에 요구되는 최소기능 추출 후 인터뷰를 통해 추출된 지시동작을 분석하는 기초적 연구이다. 이를 통해 디지털 TV에서 요구되어지는 특정 기능에 대한 동작모형을 제시하여 이에 적합한 인터페이스 환경을 디자인하는데 대한 기초자료로 활용하고자 한다.

• 한국컴퓨터정보학회논문지
• /
• 제26권6호
• /
• pp.47-53
• /
• 2021

본 논문에서는 단일 팬 방식 홀로그램 디스플레이의 제한된 시야각 문제점을 개선하기 위한 멀티비전 기반 홀로그램 디스플레이를 제안한다. 기존 단일 팬 방식의 디스플레이는 시야각이 좁고 팬의 길이가 길어짐으로 인한 낮은 해상도의 문제점을 가진다. 또한, SD 카드 사용으로 인한 데이터 변경의 어려움을 Wi-Fi 방식으로 데이터를 송신하기 위한 전용 앱을 구현하고자 한다. 본 논문에서는 3개의 REG LED 팬으로 구성된 디스플레이를 설계하고 구현하였다. 앱을 이용한 영상송신 결과, 광고 및 시연 등의 상업적 용도로 사용할 수 있음을 확인하였다. 본 연구의 결과는 멀티비전 홀로그램의 대중화에 많은 도움이 될 것으로 사료된다.

• International Journal of Computer Science & Network Security
• /
• 제22권12호
• /
• pp.217-228
• /
• 2022

The study aimed to build an electronic strategy in innovative learning situations for the role of education in combating intellectual currents. A total of 525 Saudi university faculty members and general education teachers were surveyed using two electronic questionnaires. Arithmetic averages and standard deviations, One-way ANOVA, Scheffé's test, Pearson's correlation coefficient, and Cronbach's alpha stability coefficient were used as statistical methods. The study statistically identifies the differences between the study sample at the level of significance (0.05). and the design of a digital application for individual learning to combat deviant intellectual currents to activate them in light of Saudi Vision 2030 by combining the theoretical academic material and turning it into a learning e-game called (crosswords). The game is equipped with hyper media that supports education with entertainment to direct ideas towards the promotion of identity, the development of values towards moderation and the consolidation of intellectual security. Additionally, the learning e-game represents awareness messages in three short films to activate the role of curricula and intellectual awareness centers to apply realistically, innovatively, and effectively.

• 한국농업기계학회:학술대회논문집
• /
• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.III
• /
• pp.569-577
• /
• 2000

The position of tobacco leaves is affluence to the quality. To evaluate its quality, sample leaves was collected according to the position of attachment. In Korea, the position was divided into four classes such as high, middle, low and inside positioned leaves. Until now, the grade of standard sample was determined by human expert from korea ginseng and tobacco company. Many research were done by the chemical and spectrum analysis using NIR and computer vision. The grade of tobacco leaves mainly classified into 5 grades according to the attached position and its chemical composition. In high and low positioned leaves shows a low level grade under grade 3. Generally, inside and medium positioned leaf has a high level grade. This is the basic research to develop a real time tobacco leaves grading system combined with portable NIR spectrum analysis system. However, this research just deals with position recognition and grading using the color machine vision. The RGB color information was converted to HSI image format and the sample was all investigated using the bundle of tobacco leaves. Quality grade and position recognition was performed through well known general error back propagation neural network. Finally, the relationship about attached leaf position and its grade was analyzed.

• 한국공작기계학회논문집
• /
• 제13권3호
• /
• pp.24-29
• /
• 2004

The grinding process plays a key role which decides the quality of a product finally. But the grinding process is very irregular, so it is very difficult to analyse the process accurately. Therefore it is very important in the aspect of precision and automation to reduce the idle time and to decide the proper dressing time by watching. In this study, we choose the method which can be observed directly by using of computer vision and then apply pattern classification technique to the method of measuring the wheel surface. Pattern classification technique is proper to analyse complicated surface image. We observe the change of the wheel surface by using of the gray level run lengths which are representative in this technique.

• International Journal of Automotive Technology
• /
• 제8권4호
• /
• pp.513-520
• /
• 2007

In this paper, we propose an approach to identify the driving environment for intelligent highway vehicles by means of image processing and computer vision techniques. The proposed approach mainly consists of two consecutive computational steps. The first step is the lane marking detection, which is used to identify the location of the host vehicle and road geometry. In this step, related standard image processing techniques are adapted for lane-related information. In the second step, by using the output from the first step, a four-stage algorithm for vehicle detection is proposed to provide information on the relative position and speed between the host vehicle and each preceding vehicle. The proposed approach has been validated in several real-world scenarios. Herein, experimental results indicate low false alarm and low false dismissal and have demonstrated the robustness of the proposed detection approach.