• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.229-232
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• 2005

In this paper, an image-based "approach-align -grasp" visual servo control design is proposed for the problem of object grasping, which is based on the binocular stand-alone system. The basic idea consists of considering a vision system as a specific sensor dedicated a task and included in a control servo loop, and we perform automatic grasping follows the classical approach of splitting the task into preparation and execution stages. During the execution stage, once the image-based control modeling is established, the control task can be performed automatically. The proposed visual servoing control scheme ensures the convergence of the image-features to desired trajectories by using the Jacobian matrix, which is proved by the Lyapunov stability theory. And we also stress the importance of projective invariant object/gripper alignment. The alignment between two solids in 3-D projective space can be represented with view-invariant, more precisely; it can be easily mapped into an image set-point without any knowledge about the camera parameters. The main feature of this method is that the accuracy associated with the task to be performed is not affected by discrepancies between the Euclidean setups at preparation and at task execution stages. Then according to the projective alignment, the set point can be computed. The robot gripper will move to the desired position with the image-based control law. In this paper we adopt a constant Jacobian online. Such method describe herein integrate vision system, robotics and automatic control to achieve its goal, it overcomes disadvantages of discrepancies between the different Euclidean setups and proposes control law in binocular-stand vision case. The experimental simulation shows that such image-based approach is effective in performing the precise alignment between the robot end-effector and the object.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4903-4929
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• 2018

In this study, a fully automatic pose and expression invariant 3D face alignment algorithm is proposed to handle frontal and profile face images which is based on a two pass course to fine alignment strategy. The first pass of the algorithm coarsely aligns the face images to an intrinsic coordinate system (ICS) through a single 3D rotation and the second pass aligns them at fine level using a minimum nose tip-scanner distance (MNSD) approach. For facial recognition, multi-view faces are synthesized to exploit real 3D information and test the efficacy of the proposed system. Due to optimal separating hyper plane (OSH), Support Vector Machine (SVM) is employed in multi-view face verification (FV) task. In addition, a multi stage unified classifier based face identification (FI) algorithm is employed which combines results from seven base classifiers, two parallel face recognition algorithms and an exponential rank combiner, all in a hierarchical manner. The performance figures of the proposed methodology are corroborated by extensive experiments performed on four benchmark datasets: GavabDB, Bosphorus, UMB-DB and FRGC v2.0. Results show mark improvement in alignment accuracy and recognition rates. Moreover, a computational complexity analysis has been carried out for the proposed algorithm which reveals its superiority in terms of computational efficiency as well.

• Structural Engineering and Mechanics
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• v.91 no.5
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• pp.443-457
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• 2024

At present, the traditional concrete surface inspection methods based on artificial vision have the problems of high cost and insecurity, while the computer vision methods rely on artificial selection features in the case of sensitive environmental changes and difficult promotion. In order to solve these problems, this paper introduces deep learning technology in the field of computer vision to achieve automatic feature extraction of structural damage, with excellent detection speed and strong generalization ability. The main contents of this study are as follows: (1) A method based on DeepLabV3+ convolutional neural network model is proposed for surface detection of post-earthquake structural damage, including surface damage such as concrete cracks, spaling and exposed steel bars. The key semantic information is extracted by different backbone networks, and the data sets containing various surface damage are trained, tested and evaluated. The intersection ratios of 54.4%, 44.2%, and 89.9% in the test set demonstrate the network's capability to accurately identify different types of structural surface damages in pixel-level segmentation, highlighting its effectiveness in varied testing scenarios. (2) A semantic segmentation model based on DeepLabV3+ convolutional neural network is proposed for the detection and evaluation of post-earthquake structural components. Using a dataset that includes building structural components and their damage degrees for training, testing, and evaluation, semantic segmentation detection accuracies were recorded at 98.5% and 56.9%. To provide a comprehensive assessment that considers both false positives and false negatives, the Mean Intersection over Union (Mean IoU) was employed as the primary evaluation metric. This choice ensures that the network's performance in detecting and evaluating pixel-level damage in post-earthquake structural components is evaluated uniformly across all experiments. By incorporating deep learning technology, this study not only offers an innovative solution for accurately identifying post-earthquake damage in civil engineering structures but also contributes significantly to empirical research in automated detection and evaluation within the field of structural health monitoring.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.63-66
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• 2021

The technological advancement in computer vision has made system like grab-and-go grocery a reality. Now all the shoppers have to do now is to walk in grab the items and go out without having to wait in the long queues. This paper presents an intelligent retail environment system that is capable of monitoring and tracking customer's activity during shopping based on their interaction with the shelf. It aims to develop a system that is low cost, easy to mount and exhibit adequate performance in real environment.

• Journal of Drive and Control
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• v.21 no.1
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• pp.53-58
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• 2024

With the recent development of intelligence and automation technologies for construction machinery, the demand for safety and efficiency of road-cutting operations has continued to increase. In response to this, a double-blade road cutter has been developed that can automatically cut roads. However, a double-blade road cutter has a load difference between the two blades due to the ground and wear conditions of the cutting blades. The difference in load between the two blades distorts the direction of travel of the cutter. In this study, a vision sensor-based driving guide technology was developed to correct the driving path of road cutters. In addition, we developed a load-sensing technology that detects blade loads in real-time and controls driving speed in the event of overload.

• Journal of Sensor Science and Technology
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• v.15 no.2
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• pp.112-119
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• 2006

Resolution of an image sensor is very significant parameter to improve. It is hard to improve the resolution of the CMOS vision chip for edge detection based on a biological retina using a resistive network because the vision chip contains additional circuits such as a resistive network and some processing circuits comparing with general image sensors such as CMOS image sensor (CIS). In this paper, we proved the problem of low resolution by separating photo-sensing and signal processing circuits. This type of vision chips occurs a problem of low operation speed because the signal processing circuits should be commonly used in a row of the photo-sensors. The low speed problem of operation was proved by using a reset decoder. A vision chip for edge detection with $128{\times}128$ pixel array has been designed and fabricated by using $0.35{\mu}m$ 2-poly 4-metal CMOS technology. The fabricated chip was integrated with optical lens as a camera system and investigated with real image. By using this chip, we could achieved sufficient edge images for real application.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.10
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• pp.949-957
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• 2017

A laser-vision-based height measurement system is developed and implemented for the inspection of two-step variable valve lift module assemblies. The proposed laser-vision sensor module is designed based on the principle of laser triangulation. This paper summarizes the work on 3D point cloud data collection and height difference measurements. The configuration of the measurement system and the proposed height measurement algorithm are described and analyzed in detail. Additional measurement experiments on the height differences of valves and lash adjusters of a two-step variable valve lift module were implemented repeatedly to evaluate the accuracy and repeatability of the proposed measurement system. Experimental results show that the proposed laser-vision-based height measurement system achieves high accuracy, repeatability, and stabilization for the inspection of two-step variable valve lift module assemblies.

• Journal of Sensor Science and Technology
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• v.32 no.5
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• pp.320-327
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• 2023

In this study, an FPGA-based sealer inspection system was developed to inspect the sealer applied to install vehicle glass on a car body. The sealer is a liquid or paste-like material that promotes adhesion such as sealing and waterproofing for mounting and assembling vehicle parts to a car body. The system installed in the existing vehicle design parts line does not detect the sealer in the glass rotation section and takes a long time to process. This study developed a line laser camera sensor and an FPGA vision signal processing module to solve this problem. The line laser camera sensor was developed such that the resolution and speed of the camera for data acquisition could be modified according to the irradiation angle of the laser. Furthermore, it was developed considering the mountability of the entire system to prevent interference with the sealer ejection machine. In addition, a vision signal processing module was developed using the Zynq-7020 FPGA chip to improve the processing speed of the algorithm that converted the profile to the sealer shape image acquired from a 2D camera and calculated the width and height of the sealer using the converted profile. The performance of the developed sealer application inspection system was verified by establishing an experimental environment identical to that of an actual automobile production line. The experimental results confirmed the performance of the sealer application inspection at a level that satisfied the requirements of automotive field standards.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.627-632
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• 2016

In this paper, we propose a new vision-based defect inspection system for the surface of hot slabs. To minimize the influence of self-emission from slab surfaces with high temperature, an optic method based on blue LED light and a blue pass filter is proposed. Because the slab surface is partially covered with scales, which are unavoidable oxidized substances caused during manufacturing, it is difficult to distinguish between vertical cracks and scale. In order to resolve this problem and to improve the detection performance, the use of a Gabor filter and dynamic programming are proposed. Finally, the effectiveness of the proposed method is shown by means of experiments conducted on images of hot slabs that were obtained from an actual slab production line.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1102-1105
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• 2004

In this paper, the problem of a viewer's head tracking in a desktop-based interactive stereoscopic display system is considered. A fast and low-cost approach to the problem is important for such a computing environment. The system under consideration utilizes a shuttle glass for stereoscopic display. The proposed method makes use of an image taken from a single low-cost video camera. By using a simple feature extraction algorithm, the obtained points corresponding to the image of the user-worn shuttle glass are used to estimate the glass center, its local 'yaw' angle, as measured with respect to the glass center, and its global 'yaw' angle as measured with respect to the camera location. With these estimations, the stereoscopic image synthetic program utilizes those values to interactively adjust the two-view stereoscopic image pair as displayed on a computer screen. The adjustment is carried out such that the so-obtained stereoscopic picture, when viewed from a current user position, provides a close-to-real perspective and depth perception. However, because the algorithm and device used are designed for fast computation, the estimation is typically not precise enough to provide a flicker-free interactive viewing. An error concealment method is thus proposed to alleviate the problem. This concealment method should be sufficient for applications that do not require a high degree of visual realism and interaction.