• Proceedings of the KIEE Conference
• /
• 1986.07a
• /
• pp.97-109
• /
• 1986

The ultimate goal of an industrial robot is to make full use of its real ability to communicate with any given intelligent device, and to do so independently of hardware, architecture and languages. This paper describes the necessary functions of a robot used in an integrated manufacturing system, and the basic philosophy of organization as applied to the robot controller. An example of a machine vision system called MYVIS is reviewed in relation to MAP and LAN in a practical cell application.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2000.10a
• /
• pp.683-687
• /
• 2000

Lighting is the most critical aspect of any machine vision application. Choosing the proper lighting scheme can result in increased accuracy, system reliablity, and response time. Many goof applications have failed for the lack of appropriate lighting. It is a serious and costly mistake to assume that inadequate lighting can be compensated for in an algorithm Therefore, this paper will cover the most commonly used forms of lighting methods.

• Proceedings of the KIEE Conference
• /
• 2000.07d
• /
• pp.3056-3059
• /
• 2000

This paper describes a fast image labeling algorithm for the feature extraction of connected components. Labeling the connected regions of a digitized image is a fundamental computation in image analysis and machine vision, with a large number of application that can be found in various literature. This algorithm is designed for the surface defect inspection of Cold Mill Strip. The labeling algorithm permits to separate all of the connected components appearing on the Cold Mill Strip.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.11
• /
• pp.1156-1161
• /
• 2006

This paper describes a fast image labeling algorithm for the feature extraction of connected components. Labeling the connected regions of a digitized image is a fundamental computation in image analysis and machine vision, with a large number of application that can be found in various literature. This algorithm is designed for the surface defect inspection of Cold Mill Strip. The labeling algorithm permits to separate all of the connected components appearing on the Cold Mill Strip.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.20 no.5
• /
• pp.666-672
• /
• 2011

In this paper, we describes the development of automatic inspection system for detecting the defects on photovoltaic wafer by using machine vision. Until now, The defect inspection process was manually performed by operators. So these processes caused the produce of poorly-made articles and inaccuracy results. To improve the inspection accuracy, the inspection system is not only configured, but the image processing algorithm is also developed. The inspection system includes dimensional verification and pattern matching which compares a 2-D image of an object to a pattern image the method proves to be computationally efficient and accurate for real time application and we confirmed the applicability of the proposed method though the experience in a complex environment.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2000.04a
• /
• pp.115-120
• /
• 2000

This study is on the application the image processing algorithm for inspection of the aluminium mill strip surface defect. The image of surface defect data was obtained using the CCD camera with the digital signal board. The edge was found from the difference of pixel intensity between the normal image and defect image. Two step were taken to find the edge in the image processing algorithm. First, noise was removed by using the median filter in the image. Second, the edge was sharpened in detail by using the sharpening convolution filter in the image. Canny algorithm was used to defect the exact edge. The defect section was separated from the original image is to find the coordination point p1 and p2 which include the defect image

• Journal of Sensor Science and Technology
• /
• v.32 no.2
• /
• pp.124-130
• /
• 2023

Implementing flexible production systems in domestic and foreign automotive design parts assembly has increased demand for automation and power reduction. Consequently, transition to a hybrid production method is observed where multiple vehicles are assembled in a single assembly line. Multiple robots, 3D vision sensors, mounting positions, and correction software have complex configurations in the automotive glass mounting system. Hence, automation is required owing to significant difficulty in the assembly process of automobile parts. This study presents a primer lighting and inspection algorithm that is robust to the assembly environment of real automotive design parts using high power 'ㄷ'-shaped LED inclined lighting. Furthermore, a 2D camera was developed in the primer coating inspection system-the core technology of the glass mounting system. A primer application demo line applicable to the actual automobile production line was established using the proposed high power lighting and algorithm. Furthermore, application inspection performance was verified using this demo system. Experimental results verified that the performance of the proposed system exceeded the level required to satisfy the automobile requirements.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.17 no.1
• /
• pp.31-37
• /
• 2024

In this study, we propose a machine vision-based pedestrian signal detection algorithm that operates efficiently even in computing resource-constrained environments. This algorithm demonstrates high efficiency within limited resources and is designed to minimize the impact of ambient lighting by sequentially applying HSV color space-based image processing, binarization, morphological operations, labeling, and other steps to address issues such as light glare. Particularly, this algorithm is structured in a relatively simple form to ensure smooth operation within embedded system environments, considering the limitations of computing resources. Consequently, it possesses a structure that operates reliably even in environments with low computing resources. Moreover, the proposed pedestrian signal system not only includes pedestrian signal detection capabilities but also incorporates IoT functionality, allowing wireless integration with a web server. This integration enables users to conveniently monitor and control the status of the signal system through the web server. Additionally, successful implementation has been achieved for effectively controlling 50W LED pedestrian signals. This proposed system aims to provide a rapid and efficient pedestrian signal detection and control system within resource-constrained environments, contemplating its potential applicability in real-world road scenarios. Anticipated contributions include fostering the establishment of safer and more intelligent traffic systems.

• Journal of Biosystems Engineering
• /
• v.22 no.2
• /
• pp.137-150
• /
• 1997

To investigate the feasibility of a boom sprayer in the paddy field, an experimental boom sprayer for both broadcast and directed spraying to the lower part of rice plants was developed. The droplet deposition characteristics of the boom sprayers were experimentally compared to those of power sprayer. Water sensitive papers(WSP) and a machine vision system were used to evaluate the coverage rate and droplet density. It was shown that the broadcast application by the boom sprayer was the best coverage among the tested sprayers. Coverage tate and droplet density were affected by the distance between nozzles and the sprayer ground speed, The best result was obtained when the distance of 30cm and the speed of 1.7km/hr. The directed application showed inconsistency in overall droplet distribution. The inconsistency was judged to be caused by conflict between plants and boom extenders. The power sprayer showed a very wide range of droplet size distribution, relatively larger droplets and inconsistency in cove The power sprayer was judged to be inadequate for the low-volume precision application because of inconsistency in performance and difficulty in adjusting the spraying rate. Based on the droplet coverage characteristics, it was concluded that the self-propelled boom sprayer for the broadcast application was feasible for an alternative to the power sprayer in case of low volume, precision application in paddy condition.

• Journal of Digital Contents Society
• /
• v.19 no.3
• /
• pp.435-443
• /
• 2018

Recently, with the explosive development of computing power, various methods such as RNN and CNN have been proposed under the name of Deep Learning, which solve many problems of Computer Vision have. The Generative Adversarial Network, released in 2014, showed that the problem of computer vision can be sufficiently solved in unsupervised learning, and the generation domain can also be studied using learned generators. GAN is being developed in various forms in combination with various models. Machine learning has difficulty in collecting data. If it is too large, it is difficult to refine the effective data set by removing the noise. If it is too small, the small difference becomes too big noise, and learning is not easy. In this paper, we apply a deep CNN model for extracting facial region in image frame to GAN model as a preprocessing filter, and propose a method to produce composite images of various facial expressions by stably learning with limited collection data of two persons.