• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.43-49
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• 2015

Maximum lock-on distance in tactical guidance missile using seeker image is estimated by seeker's FOV, resolution and performance of tracking algorithm. In case, a missile is launched beyond the maximum lock-on distance, the missile is guided by INS pure navigation until it enters the lock-on possible zone. However, the probability of a target's existence within seekers images decreases as flight time goes by. Therefore, it is crucial to determine the distance that satisfies a certain target existence probability (TEP) and the maximum lock-on distance in order for an operator to take over the navigation role between two distances. In this paper, simulation which can analyse TEP in tactical guided missile seeker image is designed.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.503-508
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• 2003

Since surgical treatment of the spine should overcome neurological compromises, the operative procedures need to be carefully planned and carried out with high degree of precision. Percutaneous vertebroplasty is a surgical procedure that was introduced for the treatment of compression fracture of the vertebrae. This procedure includes puncturing vertebrae and filling with polymethylmethacrylate (PMMA). Recent studies have shown that the procedure could provide structural reinforcement for the osteoporotic vertebrae while being minimally invasive and safe with immediate relief of pain. However, failures of treatment due to excessive PMMA volume injection have been reported as one of complications in vertebroplasty. It is believed that the control of PMMA volume is one of the most critical factors that can reduce the incidence of complications. Therefore, clinical success of vertebroplasty can be dependent on the volume of PMMA injection for a given patient. In this study, the optimal volume of PMMA injection for vertebroplasty was predicted based on the image analysis of a given patient.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.144-148
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• 2005

The goal of this work is to develop and test a robot-assisted surgery system for spinal fusion. The system is composed of a robot, a surgical planning system, and a navigation system. It plays the role of assisting surgeons for inserting a pedicle screw in the spinal fusion procedure. Compared to conventional methods fer spinal fusion, the proposed surgical procedure ensures minimum invasion and better accuracy by using robot and image information. The robot plays the role of positioning and guiding needles, drills, and other surgical instruments or conducts automatic boring and screwing. Pre-operative CT images and intra-operative fluoroscopic images are integrated to provide the surgeon with information for surgical planning. Several experiments employing the developed robotic surgery system are conducted. The experimental results confirmed that the system is not only able to guide the surgical tools by accurately pointing and orienting the specified location, but also successfully compensate the movement of the patient due to his/her respiration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2068-2082
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• 2023

With the rapid development of deep learning, Depth Map Super-Resolution (DMSR) method has achieved more advanced performances. However, when the upsampling rate is very large, it is difficult to capture the structural consistency between color features and depth features by these DMSR methods. Therefore, we propose a color-image guided DMSR method based on iterative depth feature enhancement. Considering the feature difference between high-quality color features and low-quality depth features, we propose to decompose the depth features into High-Frequency (HF) and Low-Frequency (LF) components. Due to structural homogeneity of depth HF components and HF color features, only HF color features are used to enhance the depth HF features without using the LF color features. Before the HF and LF depth feature decomposition, the LF component of the previous depth decomposition and the updated HF component are combined together. After decomposing and reorganizing recursively-updated features, we combine all the depth LF features with the final updated depth HF features to obtain the enhanced-depth features. Next, the enhanced-depth features are input into the multistage depth map fusion reconstruction block, in which the cross enhancement module is introduced into the reconstruction block to fully mine the spatial correlation of depth map by interleaving various features between different convolution groups. Experimental results can show that the two objective assessments of root mean square error and mean absolute deviation of the proposed method are superior to those of many latest DMSR methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4405-4418
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• 2016

Automatic image completion techniques have difficulty processing images in which the target region has multiple planes or is non-facade. Here, we propose a new image completion method that uses belief propagation based on planar priorities. We first calculate planar information, which includes planar projection parameters, plane segments, and repetitive regularity extractions within the plane. Next, we convert this planar information into planar guide knowledge using the prior probabilities of patch transforms and offsets. Using the energy of the discrete Markov Random Field (MRF), we then define an objective function for image completion that uses the planar guide knowledge. Finally, in order to effectively optimize the MRF, we propose a new optimization scheme, termed Planar Priority-belief propagation that includes message-scheduling-based planar priority and dynamic label cropping. The results of experiment show that our approach exhibits advanced performance compared with existing approaches.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.91-97
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• 2005

Bones are dynamic structures, being supported by muscles, tendons, and ligaments. When some or all the structures are disturbed i.e. in fractures, the alignment of the bone in respect to the rest of the body is deranged. This gives rise to axial as well as rotational deformity in three dimensional planes. The correct alignment and position of the long bones are to be maintained to heal the bone in the best possible anatomical and functional position. The objective of this research is to address the problems in the current practice involving surgeon, assistant, fluoroscopy and crude mechanical means and to see if a robotic solution exists to solve the problems of manipulating and reducing long bone fractures. This paper presents various design aspects of the proposed surgeon-instructed, image-guided and robotic system including the system design specification, robot design and analysis, motion control and implementation, and x-ray image processing and incorporation in CAD environment.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.923-928
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• 1990

This paper describes the design and implementation of a real-time, high-precision vision system and its application to SMT(surface mounting technology) automation. The vision system employs a 32 bit MC68030 as a main processor, and consists of image acquisition unit. DSP56001 DSP based vision processor, and several algorithmically dedicated hardware modules. The image acquisition unit provides 512*480*8 bit image for high-precision vision tasks. The DSP vision processor and hardware modules, such as histogram extractor and feature extractor, are designed for a real-time excution of vision algorithms. Especially, the implementation of multi-processing architecture based on DSP vision processors allows us to employ more sophisticated and flexible vision algorithms for real-time operation. The developed vision system is combined with an Adept Robot system to form a complete SMD system. It has been found that the vision guided SMD assembly system is able to provide a satisfactory performance for SND automation.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.42-46
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• 2012

A simple and accurate depth estimation algorithm for an IBVS (Image-Based Visual Servoing) is presented. Specifically, this algorithm is useful for under-actuated systems such as visual-guided quadrotor UAVs (Unmanned Aerial Vehicles). Since the image of a marker changes with changing pitch and roll angles of quadrotor, it is difficult to estimate depth. The proposed algorithm compensates a shape of the marker, so that the system acquire more accurate depth information without complicated processes. Also, the roll and pitch channels are decoupled so that the IBVS algorithm can be used in an under-actuated quadrotor system.

• Journal of Applied and Pure Mathematics
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• v.5 no.5_6
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• pp.389-406
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• 2023

In the pursuit of enhancing image fusion techniques, this research presents a novel approach for fusing multimodal images, specifically infrared (IR) and visible (VIS) images, utilizing a combination of partial differential equations (PDE) and discrete cosine transformation (DCT). The proposed method seeks to leverage the thermal and structural information provided by IR imaging and the fine-grained details offered by VIS imaging create composite images that are superior in quality and informativeness. Through a meticulous fusion process, which involves PDE-guided fusion, DCT component selection, and weighted combination, the methodology aims to strike a balance that optimally preserves essential features and minimizes artifacts. Rigorous evaluations, both objective and subjective, are conducted to validate the effectiveness of the approach. This research contributes to the ongoing advancement of multimodal image fusion, addressing applications in fields like medical imaging, surveillance, and remote sensing, where the marriage of IR and VIS data is of paramount importance.

• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.21-29
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• 2019

This paper proposes a novel framework for image fusion of satellite imagery to enhance spatial resolution of the image via structure-texture decomposition. The resolution of the satellite imagery depends on the sensors, for example, panchromatic images have high spatial resolution but only a single gray band whereas multi-spectral images have low spatial resolution but multiple bands. To enhance the spatial resolution of low-resolution images, such as multi-spectral or infrared images, the proposed framework combines the structures from the low-resolution image and the textures from the high-resolution image. To improve the spatial quality of structural edges, the structure image from the low-resolution image is guided filtered with the structure image from the high-resolution image as the guidance image. The combination step is performed by pixel-wise addition of the filtered structure image and the texture image. Quantitative and qualitative evaluation demonstrate the proposed method preserves spectral and spatial fidelity of input images.