• Journal of Biosystems Engineering
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• v.23 no.5
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• pp.481-490
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• 1998

A computer vision system to measure low flow rate of solid particles was developed and tested to examine its performance with various sized 7 kinds of seeds, perilla, mung bean, paddy, small red bean, black soybean, Cuba bean and small potato tuber. The test was performed for two types of particle flow, continuous and discontinuous. For the continuous flow tested with perilla, mung bean and paddy, the tests resulted correlation coefficients for the flow rates measured by the computer vision and direct method about 0.98. Average errors of the computer vision measurement were in a range of 6∼9%. For the discontinuous flow tested with small red bean, black soybean, Cuba bean and small potato tuber, the tests resulted correlation coefficients for the flow rates measured by the computer vision and direct method 0.98∼0.99. Average errors of the computer vision measurement were in a range of 5∼10%. Performance of the computer vision system was compared with that of the conventional optical sensor to count particles in discontinuous flow. The comparison was done with black soybean, Cuba bean and small potato tuber, and resulted that the computer vision has much better performance than the optical sensor in a sense of precision of the measurement.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.285-288
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• 2005

We propose a novel programmable miniature vision module based on a custom designed analog VLSI (aVLSI) chip. The vision module consists of the optical flow vision sensor embedded with commercial off-the-shelves digital hardware; in our case is the Intel XScale PXA270 processor enforced with a programmable gate array device. The aVLSI sensor provides gray-scale imager data as well as smooth optical flow estimates, thus each pixel gives a triplet of information that can be continuously read out as three independent images. The particular computational architecture of the custom designed sensor, which is fully parallel and also analog, allows for efficient real-time estimations of the smooth optical flow. The Intel XScale PXA270 controls the sensor read-out and furthermore allows, together with the programmable gate array, for additional higher level processing of the intensity image and optical flow data. It also provides the necessary standard interface such that the module can be easily programmed and integrated into different vision systems, or even form a complete stand-alone vision system itself. The low power consumption, small size and flexible interface of the proposed vision module suggests that it could be particularly well suited as a vision system in an autonomous robotics platform and especially well suited for educational projects in the robotic sciences.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.56-59
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• 1997

Vision system is mainly consist of three parts of perception, action. One of these parts, perception system detects visual target in surrounding environment. Block-based motion estimation with compensation is one of the popular approaches without accuracy. The hierarchical method the optical flow with gradient is used to improve optical flow time delay.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.881-884
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• 2000

Foveated vision has the big advantage of exhibiting a wide field of view, along with a high resolution fovea. However, in the case of using optical flow, foveated vision kas one demerit. The demerit is a concentrate of optical flow. For foveated vision, an object moves almost only around the center of the field. In this paper, we suggest how to segment motion of some objects, and how to discriminate a hand and another object. In the future, the method we suggested may be useful for recognizing human actions by foveated vision.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.2
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• pp.133-139
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• 2013

This paper proposes a vision-based indoor localization method for autonomous vehicles. A single upward-facing digital camera was mounted on an autonomous vehicle and used as a vision sensor to identify artificial landmarks and any natural corner features. An interest point detector was used to find the natural features. Using an optical flow detection algorithm, information related to the direction and vehicle translation was defined. This information was used to track the vehicle movements. Random noise related to uneven light disrupted the calculation of the vehicle translation. Thus, to estimate the vehicle translation, a Kalman filter was used to calculate the vehicle position. These algorithms were tested on a vehicle in a real environment. The image processing method could recognize the landmarks precisely, while the Kalman filter algorithm could estimate the vehicle's position accurately. The experimental results confirmed that the proposed approaches can be implemented in practical situations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.3
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• pp.267-274
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• 2009

Recently, UAVs (Unmanned Aerial Vehicles) are expected much as the Unmanned Systems for various missions. These missions are often based on the Vision System. Especially, missions such as surveillance and pursuit have a process which is carried on through the transmitted vision data from the UAV. In case of small UAVs, monocular vision is often used to consider weights and expenses. Research of missions performance using the monocular vision is continued but, actually, ground and target model have difference in distance from the UAV. So, 3D distance measurement is still incorrect. In this study, Mean-Shift Algorithm, Optical Flow and Subspace Method are posed to estimate the relative depth. Mean-Shift Algorithm is used for target tracking and determining Region of Interest (ROI). Optical Flow includes image motion information using pixel intensity. After that, Subspace Method computes the translation and rotation of image and estimates the relative depth. Finally, we present the results of this study using images obtained from the UAV experiments.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.4
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• pp.268-273
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• 2003

In the present study, the characteristics of upward bubble flow were experimentally investigated in a liquid bath. An electro-conductivity probe was used to measure local volume fraction and bubble frequency. Since the gas is concentrated at the near nozzle, the flow parameters are high near the nozzle. In general their axial and radial values tended to decrease with increasing distance. For visualization of flow characteristics, a Particle Image Velocimetry (P.I..V) and a thermo-vision camera were used in the present study. The experimental results show that heat transfer from bubble surface to water is largely completed within z=10mm from the nozzle, and then the temperature of bubble surface reaches that of water rapidly. Due to the centrifugal force, the flow was more developed near the wall than at bubble-water plume. Vortex flow in the bottom region was relatively weaker than that in the upper region.

• International Journal of Air-Conditioning and Refrigeration
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• v.13 no.1
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• pp.44-50
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• 2005

In the present study, the characteristics of upward bubble flow were experimentally investigated in a liquid bath. An electro-conductivity probe was used to measure local volume fraction and bubble frequency. Since the gas was concentrated at the near the nozzle, the flow parameters were high near the nozzle. In general their axial and radial values tended to decrease with increasing distance. For visualization of flow characteristics, a Particle Image Velocimetry (PIV) and a thermo-vision camera were used in the present study. The experimental results showed that heat transfer from bubble surface to water was largely completed within z = 10 mm from the nozzle, and then the temperature of bubble surface reached that of water rapidly. Due to the centrifugal force, the flow was more developed near the wall than at bubble-water plume. Vortex flow in the bottom region was relatively weaker than that in the upper region.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.1
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• pp.1-15
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• 1986

Optic flow is 2D velocity projected on the image plane of 3D velocity of a moving surface element. In this paper, we survey techniques computing optic flows from an image time sequence of moving objects and techniques determining 3D velocities and surface structures of the moving objects from the optic flows determined.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.17-32
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• 2022

This study explored an approach to estimate a flow-density diagram(FD) on a link in highway traffic environment by utilizing probe vehicles' time headway records. To study empirical flow-density diagram(EFD), the probe vehicles with vision sensors were recruited for collecting driving records for nine months and the vision sensor data pre-processing and GIS-based map matching were implemented. Then, we examined the new EFDs to evaluate validity with reference diagrams which is derived from loop detection traffic data. The probability distributions of time headway and distance headway as well as standard deviation of flow and density were utilized in examination. As a result, it turned out that the main factors for estimation errors are the limited number of probe vehicles and bias of flow status. We finally suggest a method to improve the accuracy of EFD model.