• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 1998.06b
• /
• pp.291-300
• /
• 1998

• Journal of the Korean Institute of Landscape Architecture
• /
• v.25 no.3
• /
• pp.56-65
• /
• 1997

This research was conducted to suggest some directions for desirable urban green space planning through 1) establishing a new classification system by examining the existing concept, problems and characteristics of green space and 2) defining the essence of green space environment and finding some analytical and evaluative methods through a clear establishment of functions, indicators of green space. In the research, measurements of the amount of green space was accompanied with measurements of green covered space, green volume, and the structure of greenery within the frame of vision. As result, three-dimensional measurement was possible, three-dimensional measurement was possible, which turned out to be more effective than the existing 2-dimensional measuring method. It is found that the ratio of green covered space is to proportional to the ratio of green volume in this study. Therefore in green space planning process it is desirable to consider the ratio of green volume all together.

• Current Optics and Photonics
• /
• v.6 no.2
• /
• pp.161-170
• /
• 2022

Three-dimensional (3D) geometric models are introduced to correct vignetting, and a downhill simplex search is applied to determine the coefficients of a 3D model used in digital microscopy. Vignetting is nonuniform illuminance with a geometric regularity on a two-dimensional (2D) image plane, which allows the illuminance distribution to be estimated using 3D models. The 3D models are defined using generalized polynomials and arbitrary coefficients. Because the 3D models are nonlinear, their coefficients are determined using a simplex search. The cost function of the simplex search is defined to minimize the error between the 3D model and the reference image of a standard white board. The conventional and proposed methods for correcting the vignetting are used in experiments on four inspection systems based on machine vision and microscopy. The methods are investigated using various performance indices, including the coefficient of determination, the mean absolute error, and the uniformity after correction. The proposed method is intuitive and shows performance similar to the conventional approach, using a smaller number of coefficients.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.652-657
• /
• 1991

Up to date, application areas of mobile robots have been expanded. In addition, Many types of LRF(Laser Range Finder) systems have been developed to acquire three dimensional information about unknown environments. However in real world, because of various noises (sunlight, fluorescent light), it is difficult to separate reflected laser light from these noise. To overcome the previous restriction, we have developed a new type vision system which enables a mobile robot to measure the distance to a object located 1-5 (m) ahead with an error than 2%. The separation and detection algorithm used in this system consists of pulse phase difference method and multi-stripe structured light. The effectiveness and feasibility of the proposed vision system are demonstrated by 3-D maps of detected objects and computation time analysis.

• Journal of Institute of Control, Robotics and Systems
• /
• v.15 no.12
• /
• pp.1223-1231
• /
• 2009

We derive a systematic and iterative calibration algorithm, and position and pose estimation algorithm for the mobile robots in formation system based on the vision system. In addition, we develop a coordinate matching algorithm which calculates matched sequence of order in both extracted image coordinates and object coordinates for non interactive calibration and pose estimation. Based on the results of calibration, we also develop a camera simulator to confirm the results of calibration and compare the results of simulations with those of experiments in position and pose estimation.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.7 no.3
• /
• pp.216-220
• /
• 2007

Camera calibration in machine vision is the process of determining the intrinsic camera parameters and the three-dimensional (3D) position and orientation of the camera frame relative to a certain world coordinate system. On the other hand, Takagi-Sugeno-Kang (TSK) fuzzy system is a very popular fuzzy system and approximates any nonlinear function to arbitrary accuracy with only a small number of fuzzy rules. It demonstrates not only nonlinear behavior but also transparent structure. In this paper, we present a novel and simple technique for camera calibration for machine vision using TSK fuzzy model. The proposed method divides the world into some regions according to camera view and uses the clustered 3D geometric knowledge. TSK fuzzy system is employed to estimate the camera parameters by combining partial information into complete 3D information. The experiments are performed to verify the proposed camera calibration.

• Journal of Radiation Industry
• /
• v.7 no.2_3
• /
• pp.121-126
• /
• 2013

The new algorithm technique is necessary to incorporate for analyzing and evaluating extreme condition like a nuclear accident. In this study, the combined methodology for measuring the three-dimensional space was compared with SIFT (Scale Invariant Feature Transform) and SURF (Speeded-Up Robust Feature) algorithm. The suggested method can be used for the acquisition of spatial information using the robot vision in the districted area of the nuclear facilities. As a result, these data would be helpful for identify the damaged part, degree of damage and determination of recovery sequences.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.6
• /
• pp.59-66
• /
• 1993

Stereo vision is useful in obtaining three dimensional depth information from two images taken from different view points. Neural network modeling for stereo matching, the key step in stereo vision, is defined by an energy function satisfying with three constraints proposed by Marr and Poggio. Stereo matching is then carried out through the network to find minimum energy corresponding to the optimized solution of the problem. An algorithm for stereo matching using an analog neural network is presented here. The network can reduce errors in initial state an early iteration steps by adoption of continuous sigmoid function in stead of binary state. The experimental results show good matching performance for sparse random dot stereogram and real image.

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.1
• /
• pp.21-27
• /
• 2002

Inspection and shape measurement of three-dimensional objects are widely needed in industries for quality monitoring and control. A number of visual or optical technologies have been successfully applied to measure three-dimensional surfaces. However, those conventional visual or optical methods have inherent shortcomings such as occlusion and variant surface reflection. X-ray vision system can be a good solution to these conventional problems, since we can extract the volume information including both the surface geometry and the inner structure of any objects. In the x-ray system, the surface condition of an object, whether it is lambertian or specular, does not affect the inherent characteristics of its x-ray images. In this paper, we propose a three-dimensional x-ray imaging method to reconstruct a three dimensional structure of an object out of two dimensional x-ray image sets. To achieve this by the proposed method, two or more x-ray images projected from different views are needed. Once these images are acquired, the simultaneous algebraic reconstruction technique(SART) is usually utilized. Since the existing SART algorithms have several shortcomings such as low performance in convergence and different convergence within the reconstruction volume of interest, an advanced SART algorithm named as USART(uniform SART) is proposed to avoid such shortcomings and improve the reconstruction performance. Because, each voxel within the volume is equally weighted to update instantaneous value of its internal density, it can achieve uniform convergence property of the reconstructed volume. The algorithm is simulated on various shapes of objects such as a pyramid, a hemisphere and a BGA model. Based on simulation results the performance of the proposed method is compared with that of the conventional SART method.

• The Journal of Korean Physical Therapy
• /
• v.27 no.2
• /
• pp.89-95
• /
• 2015

Purpose: The purpose of this study is to determine the effects of visual information on movement time and each angular velocity of trunk and lower extremity joints while healthy adults are in sitting and squat motion. Methods: Participants consisted of 20 healthy male and female adults; movement time and each angular velocity of trunk, pelvis, hip, knee and ankle of sitting and squat motion according to common vision, visual task and visual block were analyzed using a three dimensional motion analysis system. Results: Each angular velocity of the trunk, pelvis, hip, knee and ankle in phase 2 of the sitting showed significant difference according to the types of visual information (p<0.05). Movement time and each angular velocity of pelvis and hip in phase 2 of squat motion showed significant difference according to the types of visual information (p<0.05). According to the common vision, each angular velocity of knee and ankle in phase 1 was significantly fast in sitting (p<0.05). According to the common vision, each angular velocity of trunk, pelvis, hip, knee, and ankle in phase 2 was significantly fast in sitting (p<0.05). Conclusion: Visual information affects the angular velocity of the motion in a simple action such as sitting, and that in more complicated squat motion affects both the angular velocity and the movement time. In addition, according to the common vision, visual task and visual block, as angular velocities of all joints were faster in sitting than squat motion.