• Korean Journal of Agricultural Science
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• v.47 no.2
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• pp.315-326
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• 2020

In this study, a real-time crop recognition system was developed for an unmanned farm machine for upland farming. The crop recognition system was developed based on a stereo camera, and an image processing framework was proposed that consists of disparity matching, localization of crop area, and estimation of crop height with coordinate transformations. The performance was evaluated by attaching the crop recognition system to a tractor for five representative crops (cabbage, potato, sesame, radish, and soybean). The test condition was set at 3 levels of distances to the crop (100, 150, and 200 cm) and 5 levels of camera height (42, 44, 46, 48, and 50 cm). The mean relative error (MRE) was used to compare the height between the measured and estimated results. As a result, the MRE of Chinese cabbage was the lowest at 1.70%, and the MRE of soybean was the highest at 4.97%. It is considered that the MRE of the crop which has more similar distribution lower. the results showed that all crop height was estimated with less than 5% MRE. The developed crop recognition system can be applied to various agricultural machinery which enhances the accuracy of crop detection and its performance in various illumination conditions.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1413-1415
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• 2004

This paper proposes a SVM(Support Vector Machine) training algorithm to control a service robot with voice command. The service robot with a stereo vision system and dual manipulators of four degrees of freedom implements a User-Dependent Voice Control System. The training of SVM algorithm that is one of the statistical learning theories leads to a QP(quadratic programming) problem. In this paper, we present an efficient SVM speech recognition scheme especially based on less learning data comparing with conventional approaches. SVM discriminator decides rejection or acceptance of user's extracted voice features by the MFCC(Mel Frequency Cepstrum Coefficient). Among several SVM kernels, the exponential RBF function gives the best classification and the accurate user recognition. The numerical simulation and the experiment verified the usefulness of the proposed algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.2 s.191
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• pp.58-63
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• 2007

This paper proposes a novel method of projecting a multiple stripe pattern whose intensity profile is sinusoidal. The sinusoidal stripe patterns are plated with chromium on a piece of glass, and the glass is placed within an optical projection system. By linearly moving the glass along the direction of the stripe pattern, the projection system generates the motion blurring effect, and as a result, produces a blurred stripe pattern whose intensity profile is sinusoidal along the perpendicular direction of the stripe pattern. The sinusoidal pattern improves the measurement accuracy of phase-shifting method. Experimental results are provided for three different types of stripe patterns: rectangle, diamond, and sinusoid.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2000.04a
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• pp.129-133
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• 2000

It is reasonable to use the stereo vision and image processing technique to digitize 3D coordinates of grid points and to evaluate surface strains on a sheet metal parts. However this method has its intrinsic problems such as the difficulty in enhancement of bad images inevitable error due to digital image resolution of camera and frame grabber unreliability of strains and thickness evaluated from coarse grid on the corner area with large curvature and the limitation of the area that can be measured at a time. Therefore it is still hard to measure strain distribution over the entire surface of a medium,- or large-sized stamped part at a time even by using an automated strain measurement system. In this study the curvature correction algorithm based on the grid refinement and the geometry assembling algorithm based on the global error minimization (GEM) scheme are suggested. Several applications are presented to show the reliability and efficiency of these algorithms.

• Journal of the Korea Society of Computer and Information
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• v.1 no.1
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• pp.171-182
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• 1996

This study is, on the design and Implementation of automatic translation (user made pictures, or drawings to 3-dimentional graphics) magic eye system by analyzing and algorithm the principle of the stereogram(so called "magic. eye" ) which Is the another type of stereo images matching method. It was written in C programming language and needs windows 3.1 or higher version of windows. It Is expected to be utilized as acknowledgment tool of 3-dimentional vision and to be use In optalmology as a tool to enhance one's visualpower by general PC user. who are interested In stereogram.tereogram.

• Journal of Broadcast Engineering
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• v.16 no.6
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• pp.902-915
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• 2011

Recently in the area-based stereo matching field, Adaptive Support-Weight (ASW) method that weights matching cost adaptively according to the luminance intensity and the geometric difference shows promising matching performance. However, ASW requires more computational cost than other matching algorithms do and its real-time implementation becomes impractical. By applying Integral Histogram technique after approximating to the Bilateral filter equation, the computational time of ASW can be restricted in constant time regardless of the support window size. However, Integral Histogram technique causes loss of the matching accuracy during approximation process of the original ASW equation. In this paper, we propose a novel algorithm that maintains the ASW algorithm's matching accuracy while reducing the computational costs. In the proposed algorithm, we propose Sub-Block method that groups the pixels within the support area. We also propose the method adjusting the disparity search range depending on edge information. The proposed technique reduces the calculation time efficiently while improving the matching accuracy.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.344-352
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• 2022

Accurate indoor localization of construction workers and mobile assets is essential in safety management. Existing positioning methods based on GPS, wireless, vision, or sensor based RTLS are erroneous or expensive in large-scale indoor environments. Tightly coupled sensor fusion mitigates these limitations. This research paper proposes a state-of-the-art positioning methodology, addressing the existing limitations, by integrating Stereo Visual Inertial Odometry (SVIO) with fiducial landmarks called AprilTags. SVIO determines the relative position of the moving assets or workers from the initial starting point. This relative position is transformed to an absolute position when AprilTag placed at various entry points is decoded. The proposed solution is tested on the NVIDIA ISAAC SIM virtual environment, where the trajectory of the indoor moving forklift is estimated. The results show accurate localization of the moving asset within any indoor or underground environment. The system can be utilized in various use cases to increase productivity and improve safety at construction sites, contributing towards 1) indoor monitoring of man machinery coactivity for collision avoidance and 2) precise real-time knowledge of who is doing what and where.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.2
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• pp.69-79
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• 1994

The conventional machine vision system which has uniform rectangular grid requires tremendous amount of computation for processing and analysing an image especially in 2-D image transfermations such as scaling, rotation and 3-D reconvery problem typical in robot application environment. In this study, the imaging system with nonuiformly distributed image sensors simulating human visual system, referred to as Ploar Exponential Grid(PEG), is compared with the existing conventional uniform rectangular grid system in terms of image resolution and computational complexity. By mimicking the geometric structure of the PEG sensor cell, we obtained PEG-like images using computer simulation. With the images obtained from the simulation, image resolution of the two systems are compared and some basic image processing tasks such as image scaling and rotation are implemented based on the PEG sensor system to examine its performance. Furthermore Fourier transform of PEG image is described and implemented in image analysis point of view. Also, the range and heading-angle measurement errors usually encountered in 3-D coordinates recovery with stereo camera system are claculated based on the PEG sensor system and compared with those obtained from the uniform rectangular grid system. In fact, the PEC imaging system not only reduces the computational requirements but also has scale and rotational invariance property in Fourier spectrum. Hence the PEG system has more suitable image coordinate system for image scaling, rotation, and image recognition problem. The range and heading-angle measurement errors with PEG system are less than those of uniform rectangular rectangular grid system in practical measurement range.

• ETRI Journal
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• v.35 no.6
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• pp.1038-1047
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• 2013

Augmented reality (AR) is currently being applied actively to commercial products, and various types of intelligent AR systems combining both the Global Positioning System and computer-vision technologies are being developed and commercialized. This paper suggests an in-vehicle head-up display (HUD) system that is combined with AR technology. The proposed system recognizes driving-safety information and offers it to the driver. Unlike existing HUD systems, the system displays information registered to the driver's view and is developed for the robust recognition of obstacles under bad weather conditions. The system is composed of four modules: a ground obstacle detection module, an object decision module, an object recognition module, and a display module. The recognition ratio of the driving-safety information obtained by the proposed AR-HUD system is about 73%, and the system has a recognition speed of about 15 fps for both vehicles and pedestrians.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.331-339
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• 2016

This paper developed a home wellness robot platform to perform the roles in basic health care and life care in an aging society. A robotic platform and a sensory platform were implemented for an indoor wellness service. In the robotic platform, the precise mobility and the dexterous manipulation are not only developed in a symbiotic service-robot, but they also ensure the robot architecture of human friendliness. The mobile robot was made in the agile system, which consists of Omni-wheels. The manipulator was made in the anthropomorphic system to carry out dexterous handwork. In the sensing platform, RF tags and stereo camera were used for self and target localization. They were processed independently and cooperatively for accurate position and posture. The wellness robot platform was integrated in a real-time system. Finally, its good performance was confirmed through live indoor tests for health and life care.