• The Journal of the Korea institute of electronic communication sciences
• /
• v.8 no.3
• /
• pp.403-408
• /
• 2013

In this paper, we propose to develop an inspection system that recognizes surface cracks on the brake pad and the types of brake pads of each car during the production process, on a conveyor belt. The brake pad is made from a mixture of materials, using high-heat and pressure. Therefore, the brake pad can be cracked and damaged on the surface during production. Our goal is to develop an effective detection system and application software to detect substandard product. A shadow is generated when the artificial light shines on the damaged of the surface of pad. Using the computer vision algorithm that is proposed we can detect the substandard product. Results from experiments confrim the performance of the proposed algorithm.

• Journal of Digital Convergence
• /
• v.17 no.10
• /
• pp.233-242
• /
• 2019

Numerous space perception studies have shown that Euclidean 3-D structure cannot be recovered from binocular stereopsis, motion, combination of stereopsis and motion, or even with combined multiple sources of optical information. Humans, however, have no difficulties to perform the task-specific action despite of poor shape perception. We have applied humans skill and capabilities to artificial intelligence and computer vision but those machines are still far behind from humans abilities. Thus, we need to understand how we perceive depth in space and what information we use to perceive 3-D structure accurately to perform. The purpose of this paper was to review space perception literatures to apply humans abilities to artificial intelligence robots more advanced in future.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.4
• /
• pp.1559-1564
• /
• 2011

This study presents the development of a machine vision inspection system(MVIS) purposely for car seat frames as an alternative for human inspection. The proposed MVIS is designed to meet the demands, features and specifications of car seat frame manufacturing companies in striving for increased throughput of better quality. This computer-based MVIS is designed to perform quality measures by detecting holes, nuts and welding spots on every car seat frame in real time. In this study, the NI Vision Builder software for Automatic Inspection was used as a solution in configuring the aimed quality measurements. The techniques for visual inspection are optimized through qualitative analysis and simulation of human tolerance on inspecting car seat frames. Furthermore, this study exemplifies the incorporation of the optimized vision inspection environment to the pre-inspection and post-inspection subsystems. The system built on this proposed MVIS for car seat frames has successfully found the possible detections.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.6 no.4
• /
• pp.517-522
• /
• 2011

Conventional projection welding systems suffer from lots of defective products caused by manual handling. In this paper, we introduce a projection welding system that performs automatic identification, welding and counting of components and products. The proposed system checks the existence and identifies placement of components to be welded by a vision camera. After welding of the components, it automatically updates product counts and dressing items. We show that the proposed welding system can reduce the defect rate and improve the productivity through experimental test with a existing system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2018.11a
• /
• pp.167-169
• /
• 2018

2016 한국 전력 통계에 따르면 약 900 만개의 지지물과 130 만 킬로미터의 전력 분배용 전력선이 있으며 많은 인적 자원과 엄청난 양의 송전선에 대한 유지보수가 필요하다. 현재 전선 늘어짐에 대한 고장진단 기법 중 하나로 이동 중인 자동차에 부착된 비전 시스템을 이용한 방법이 있다. 이 방법에서 사용된 송전선 탐지 방법을 보완하여 송전선을 이미지상에서 추출한다. 본 논문에서는 인공지능을 사용하여 지지물 을 탐지하고, 지지물 사이의 거리가 멀다는 점을 극복하기 위하여 공통 특징점들이 있는 이미지들을 하나의 이미지로 붙이는 파노라마 기술을 사용하여 지지물 사이의 거리를 극복하며, 제안하는 방법으로 송전선을 탐지하고 늘어짐을 판단하는 시스템을 제안한다.

• Journal of the Society of Disaster Information
• /
• v.19 no.4
• /
• pp.916-923
• /
• 2023

Purpose: Looking at the status of fatal accidents in the construction industry in the 2022 Industrial Accident Status Supplementary Statistics, 27.8% of all fatal accidents in the construction industry are caused by construction equipment. In order to overcome the limitations of tours and inspections caused by the enlargement of sites and high-rise buildings, we plan to build a model that can extract construction equipment using computer vision technology and analyze the model's accuracy and field applicability. Method: In this study, deep learning is used to learn image data from excavators, dump trucks, and mobile cranes among construction equipment, and then the learning results are evaluated and analyzed and applied to construction sites. Result: At site 'A', objects of excavators and dump trucks were extracted, and the average extraction accuracy was 81.42% for excavators and 78.23% for dump trucks. The mobile crane at site 'B' showed an average accuracy of 78.14%. Conclusion: It is believed that the efficiency of on-site safety management can be increased and the risk factors for disaster occurrence can be minimized. In addition, based on this study, it can be used as basic data on the introduction of smart construction technology at construction sites.

• Proceedings of the Korea Multimedia Society Conference
• /
• 2012.05a
• /
• pp.28-29
• /
• 2012

IT 및 자동차 관련 기술의 융합 기술의 발전에 따라 자동차의 안전 및 운전편의 정보 제공에 대한 관심이 높아지면서 인간의 시각 및 지각의 한계를 보완해 줄 수 있는 보조 도구들에 대한 연구 및 개발이 활발히 이루어지고 있다. 그러나 기존의 컴퓨터 비전 기반 도로 교통 표지판 자동 검출 및 인식 기술들은 센싱 장비들의 가격 또는 조도와 원근감에 따른 교통 표지판의 색상과 모양 왜곡으로 인해 해당 표지판들의 검출을 어렵게 한다. 따라서 본 논문에서는 차량 내 탑재가 가능한 저가의 비전 카메라를 이용하여 교통표지판 칼라 분석 및 원근 보정을 통해 운전자에게 효과적으로 도로표지판 정보를 제공할 수 있는 검출기법을 제안한다. 실험을 통해 도로주행영상 내 도로표지판들을 효과적으로 검출할 수 있음을 확인하였다.

• Journal of Korea Society of Industrial Information Systems
• /
• v.27 no.2
• /
• pp.71-82
• /
• 2022

In order to replace the sampling tensile test of products produced in the tab welding process, which is one of the automotive battery manufacturing processes, vision inspectors are currently being developed and used. However, the vision inspection has the problem of inspection position error and the cost of improving it. In order to solve these problems, there are recent cases of applying deep learning technology. As one such case, this paper tries to examine the usefulness of applying Faster R-CNN, one of the deep learning technologies, to existing product inspection. The images acquired through the existing vision inspection machine are used as training data and trained using the Faster R-CNN ResNet101 V1 1024x1024 model. The results of the conventional vision test and Faster R-CNN test are compared and analyzed based on the test standards of 0% non-detection and 10% over-detection. The non-detection rate is 34.5% in the conventional vision test and 0% in the Faster R-CNN test. The over-detection rate is 100% in the conventional vision test and 6.9% in Faster R-CNN. From these results, it is confirmed that deep learning technology is very useful for detecting welding error of lead tabs in automobile batteries.

• Journal of the Korea Convergence Society
• /
• v.11 no.9
• /
• pp.15-20
• /
• 2020

Software-related training can be considered essential in situations where software is an important factor in national innovation, growth and value creation. As one of the implementation methods for engineering education, various education through virtual simulations that can educate difficult situations in a similar environment are being conducted. Recently, the construction of smart factories at production and manufacturing sites is spreading, and product inspections using vision systems are being conducted. However, it has many difficulties due to lack of operation technology of vision system, but it requires a lot of cost to construct the system for education of vision system. In this paper, provide an educational virtual simulation model that integrates computer and physics engine camera functions and can extract and transmit video. It is possible to generate an image of 30Hz or more at an average of 35.4FPS of the experimental results of the proposed model, and it is possible to send and receive images in a time of 22.7ms, which can be utilized in an educational virtual simulation educational environment.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.4 s.42
• /
• pp.251-259
• /
• 2006

Major telecommunication companies are leading on providing mobile contents service to customers. With changes in technology and social areas, most organizations are struggling to achieve the competitive edge over other organizations. Like others, university has the same problems to meet clients' needs to become being competitive. The research is to provide meaningful thoughts by analyzing empirical data and provide meaning information for University being competitive with IS and Mobile campus related decisions.