• Smart Structures and Systems
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• v.34 no.2
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• pp.117-127
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• 2024

A novel approach that the smart control of robotics can be realized by a fuzzy controller and an appropriate Runge-Kutta scheme in this paper. A recently proposed integral inequality is selected based on the free weight matrix, and the less conservative stability criterion is given in the form of linear matrix inequalities (LMIs). We demonstrate that this target information obtained through image processing is subjected to smart control with computer-vision robotic to Arduino, and the infrared beacon was utilized for the operation of practical illustrations. A fuzzy controller derived with a fuzzy Runge-Kutta type functions is injected into the system and then the system is stabilized asymptotically. In this study, a fuzzy controller and a fuzzy observer are proposed via the parallel distributed compensation technique to stabilize the system. This paper achieves the goal of real-time following of three vehicles and there are many areas where improvements were made. Finally, each information is transmitted to Arduino via I2C to follow the self-propelled vehicle. The proposed calculation is approved in reproductions and ongoing smart control tests.

• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.47-57
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• 2024

This paper proposes a system to efficiently manage delays caused by unmanaged and congested queues in crowded environments. Such queues not only cause inconvenience but also pose safety risks. Existing systems, relying on single-camera feeds, are inadequate for complex scenarios requiring multiple cameras. To address this, we developed a multi-vision long queue detection system that integrates multiple vision algorithms to accurately detect various types of queues. The algorithm processes real-time video data from multiple cameras, stitching overlapping segments into a single panoramic image. By combining object detection, tracking, and position variation analysis, the system recognizes long queues in crowded environments. The algorithm was validated with 96% accuracy and a 92% F1-score across diverse settings.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.790-797
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• 2001

A simple computer vision technology to measure the middle-ranged depth with a mono camera and a plain mirror is proposed. The proposed system is structured with the rotating mirror in front of the fixed mono camera. In contrast to the previous stereo vision system in which the disparity of the closer object is larger than that of the distant object, the pixel movement caused by the rotating mirror is bigger for the pixels of the distant object in the proposed system. Being inspired by such distinguished feature in the proposed system, the principle of the depth measurement based on the relation of the pixel movement and the distance of object is investigated. Also, the factors to influence the precision of the measurement are analysed. The benefits of the proposed system are low price and less chance of occlusion. The robustness for practical usage is an additional benefit of the proposed vision system.

• Journal of Biosystems Engineering
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• v.23 no.4
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• pp.381-390
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• 1998

An algorithm to extract the 3-D geometric information of a static object was developed using a set of 2-D computer vision system and a laser structured lighting device. As a structured light pattern, multi-parallel lines were used in the study. The proposed algorithm was composed of three stages. The camera calibration, which determined a coordinate transformation between the image plane and the real 3-D world, was performed using known 6 pairs of points at the first stage. Then, utilizing the shifting phenomena of the projected laser beam on an object, the height of the object was computed at the second stage. Finally, using the height information of the 2-D image point, the corresponding 3-D information was computed using results of the camera calibration. For arbitrary geometric objects, the maximum error of the extracted 3-D feature using the proposed algorithm was less than 1~2mm. The results showed that the proposed algorithm was accurate for 3-D geometric feature detection of an object.

• Journal of information and communication convergence engineering
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• v.12 no.2
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• pp.128-134
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• 2014

In this paper, we present a graphics processing unit (GPU)-based matching technique for the purpose of fast feature matching between different images. The scale invariant feature transform algorithm developed by Lowe for various feature matching applications, such as stereo vision and object recognition, is computationally intensive. To address this problem, we propose a matching technique optimized for GPUs to perform computations in less time. We optimize GPUs for fast computation of keypoints to make our system quick and efficient. The proposed method uses a self-organizing map feature matching technique to perform efficient matching between the different images. The experiments are performed on various image sets to examine the performance of the system under varying conditions, such as image rotation, scaling, and blurring. The experimental results show that the proposed algorithm outperforms the existing feature matching methods, resulting in fast feature matching due to the optimization of the GPU.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.445-446
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• 2007

The goal of this paper is accuracy improvement of appearance inspection by using image separation average value matching method. The appearance inspection of various electronic products and parts has been executed by the eyesight of human. But inspection by eyesight can't bring about uniform inspection result. Because the appearance inspection result by eyesight of human is changed by condition of physical and spirit of the checker. So machine vision inspection system is currently used to many appearance inspection fields instead of the checker. However the inspection result of machine vision is changed by the illumination of workplace. Therefore we have used a average value matching in this paper for improvement of vision inspection accuracy and could increase inspection accuracy of vision system. In other words, we made an effort for elevation of vision inspection accuracy by making the identical image separation average value of reference image and input image. Also this system has been developed only using PC, CCD Camera and Visual C++ for universal workplace.

• JSTS:Journal of Semiconductor Technology and Science
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• v.12 no.2
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• pp.212-218
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• 2012

A stereo vision is able to build three-dimensional maps of its environment. It can provide much more complete information than a 2D image based vision but has to process, at least, that much more data. In the past decade, real-time stereo has become a reality. Some solutions are based on reconfigurable hardware and others rely on specialized hardware. However, they are designed for their own specific applications and are difficult to extend their functionalities. This paper describes a vision system based on a System on a Chip (SoC) platform. A real-time stereo image correlator is implemented using Sum of Absolute Difference (SAD) algorithm and is integrated into the vision system using AMBA bus protocol. Since the system is designed on a pre-verified platform it can be easily extended in its functionality increasing design productivity. Simulation results show that the vision system is suitable for various real-time applications.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.598-602
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• 2003

In this paper, we propose the method to control the position of LDM(Linear DC Motor) using vision system. The proposed method is composed of a vision system for position detecting, and main computer calculates PID control output which is deliver to 8051 actuator circuit in serial communication. To confirm the usefulness of the proposed method, we experimented about position control of a small size LDM using CCD camera which has a performance 30frames/sec as vision system.

• Journal of Biosystems Engineering
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• v.32 no.2 s.121
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• pp.130-135
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• 2007

An on-line real time grading and sorting system for dried oak mushrooms was developed for on-site application. Quality grades of the mushrooms were determined according to an industrial specification. Three dimensional visual quality features were used for the grading. A progressive color computer vision system with white LED illumination was implemented to develop an algorithm to extract external quality patterns of the dried oak mushrooms. Cap (top) and gil (stem) surface images were acquired sequentially and side image was obtained using mirror. Algorithms for extracting size, roundness, pattern and color of the cap, thickness, color of the gil and amount of rolled edge of the dried mushroom were developed. Utilizing those quality factors normal and abnormal ones were classified and normal mushrooms were further classified into 30 different grades. The sorting device was developed using microprocessor controlled electro-pneumatic system with stainless buckets. Grading accuracy was around 97% and processing time was 0.4 s in average.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1124-1128
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• 1995

This paper presents the appplication of computer vision for the purpose of determing the position of the unknown point in the plane. The presented contrik method is estimate the six view parameters reqresenting the relationship between the image plane coordinates and the real physical coordinates. The estimation of six parameters is indispensable for transforming the 2-dimensional camera coordinates to the 3-dimensional spatial coordinates. Then, the position of unknown point is estimated based on the estimated parameters depending on the cameras. The suitability of this control scheme is demonstrated experimentally by determining of position the unknown point in the plane.