• The Journal of the Korea Contents Association
• /
• v.8 no.11
• /
• pp.182-188
• /
• 2008

The MLC(multi leaf collimator) in charge of important role in radiation therapy field recently have been exchanging from shielding block into it rapidly, owing to being convenient. However, MLC can be occurred the leakage dose of inter_leaves and the error of algorithm in imput and output from digital signal. We compared the difference of imput method to MLC made by Varian Cop. with the error and effective field induced by MLC shaper and film scanner based on XimaVision value as using MLC layer of various shapes. According to comparing standard value with them to basic MLC layer (test1-5), MLC shaper was $0{\sim}0.29cm$, $0.23{\sim}3.59cm^2$ and film scanner was $0{\sim}0.78cm$, $0.24{\sim}3.89cm^2$. At the MLC layer to be applied in clinic, MLC shaper was $0{\sim}0.54cm$, $0.04{\sim}1.68cm^2$ and film scanner was $0{\sim}0.78cm$, $0.24{\sim}3.89cm^2$. The more distance and field from axis of central line increase, the more bigger the error value increases. There is a few mm error from standard point at the process which imput various information to apply MLC in clinic. and effective field did not have variation of monitor unit and dose owing to being a few cm2 error against real field. But there are some problem to shield critical organs because some part of target volume induced by the movement of organs can be not included, therefore we have to pay attention on the process to imput MLC layer

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2001.04a
• /
• pp.271-274
• /
• 2001

The present paper deals with the development of digital contouring controller for multiaxial servosystem. Instead of coordinating the commands to the individual feed drives and implementing closed position loop control for each axis, this work is achieved by the evaluation of a optimal cross-couple compensator aimed specifically at improving contouring accuracy in multi-axial feed drives. The optimal control formulation explicitly includes the contour error in the performance index to be minimized. The contouring control is simulated for straight line. The results show that the proposed controller reduces contouring errors considerably, as compared to the conventional uncoupled control for biaxial systems.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.10a
• /
• pp.371-374
• /
• 1997

This study presents a new type of real-t~me CNC interpolator that is capable of generating cutter paths for ball-end milling of NURBS surfaces. The proposed surface interpolator comprises real-time algorithms for cutter-contact (CC) path scheduling and CC path interpolation. Especially, in this study, a new interpolator module to regulate cutting forces is developed. This proposed algorithm utilizes variable-feedrate commands according to the curvature of machined surfaces. The proposed interpolator is evaluated and compared with the conventional method based on constant feedrates through computer simulation.

• Journal of the Korean Society for Precision Engineering
• /
• v.14 no.8
• /
• pp.65-72
• /
• 1997

An asymmetrical cross-coupled compensator to improve the contouring performance is proposed. This is a refinement of the structure suggested by Koren. The position loop is closed with a proportional controller as in the uncoupled system. An additional input term proportional to the component of the contour error along the corresponding axis is included. The controller gains are chosen to give an appropriate frequency response and an optimum range for the damping ratio. The effectiveness of the proposed controller is studied by means of digital simulations of the dynamics of the drives and the controller for 4 types of command trajectories: straight line contour, cornering contour, circular contour, elliptic contour. Substantial improvement in contouring performance is obtained for a range of contouring conditions.

• KIPS Transactions on Software and Data Engineering
• /
• v.1 no.1
• /
• pp.43-54
• /
• 2012

This paper presents a new localization technique of an UGV(Unmanned Ground Vehicle) by matching ortho-edge images generated from a DSM (Digital Surface Map) which represents the 3D geometric information of an outdoor navigation environment and 3D range data which is obtained from a LIDAR (Light Detection and Ranging) sensor mounted at the UGV. Recent UGV localization techniques mostly try to combine positioning sensors such as GPS (Global Positioning System), IMU (Inertial Measurement Unit), and LIDAR. Especially, ICP (Iterative Closest Point)-based geometric registration techniques have been developed for UGV localization. However, the ICP-based geometric registration techniques are subject to fail to register 3D range data between LIDAR and DSM because the sensing directions of the two data are too different. In this paper, we introduce and match ortho-edge images between two different sensor data, 3D LIDAR and DSM, for the localization of the UGV. Details of new techniques to generating and matching ortho-edge images between LIDAR and DSM are presented which are followed by experimental results from four different navigation paths. The performance of the proposed technique is compared to a conventional ICP-based technique.

• Journal of Broadcast Engineering
• /
• v.11 no.1 s.30
• /
• pp.91-99
• /
• 2006

Pre-processing is one of image processing techniques to enhance image quality or appropriately convert a given image into another form for a specific purpose. An 8 bit depth map obtained by a depth camera usually contains a lot of noisy components caused by the characteristics of depth camera and edges are also more distorted by the quality of a source object and illumination condition comparing with edges in RGB texture image. To reduce this distortion, we use noise removing filters, but they are only able to reduce noise components, so that distorted edges of depth map can not be properly recovered. In this paper, we propose an algorithm that can reduce noise components and also enhance the quality of edges of depth map by using edges in RGB texture. Consequently, we can reduce errors in multi-view stereo image synthesis process.

• Journal of Broadcast Engineering
• /
• v.14 no.3
• /
• pp.322-331
• /
• 2009

This paper proposes an efficient data representation of stereo images using edge-based mesh optimization. Mash-based two dimensional warping for stereo images mainly depends on the performance of a node selection and a disparity estimation of selected nodes. Therefore, the proposed method first of all constructs the feature map which consists of both strong edges and boundary lines of objects for node selection and then generates a grid-based mesh structure using initial nodes. The displacement of each nodal position is iteratively estimated by minimizing the predicted errors between target image and predicted image after two dimensional warping for local area. Generally, iterative two dimensional warping for optimized nodal position required a high time complexity. To overcome this problem, we assume that input stereo images are only horizontal disparity and that optimal nodal position is located on the edge include object boundary lines. Therefore, proposed iterative warping method performs searching process to find optimal nodal position only on edge lines along the horizontal lines. In the experiments, we compare our proposed method with the other mesh-based methods with respect to the quality by using Peak Signal to Noise Ratio (PSNR) according to the number of nodes. Furthermore, computational complexity for an optimal mesh generation is also estimated. Therefore, we have the results that our proposed method provides an efficient stereo image representation not only fast optimal mesh generation but also decreasing of quality deterioration in spite of a small number of nodes through our experiments.

• Journal of the Korean Society for Precision Engineering
• /
• v.16 no.12
• /
• pp.14-23
• /
• 1999

This paper proposes a method to generate the velocity trajectory which guarantees user specified contour errors at corners for high speed and high precision motion control of CNC machines. The relation among the desired trajectory, system bandwidth and corner contour error are derived. Experiments show that the corner contour error specified by users can be guaranteed with the proposed velocity trajectory.

• Korean Journal of Remote Sensing
• /
• v.40 no.4
• /
• pp.387-396
• /
• 2024

Most very high-resolution (VHR) satellite images provide rational polynomial coefficients (RPC) data to facilitate the transformation between ground coordinates and image coordinates. However, initial RPC often contains geometric errors, necessitating correction through matching with ground control points (GCPs). A GCP chip is a small image patch extracted from an orthorectified image together with height information of the center point, which can be directly used for geometric correction. Many studies have focused on area-based matching methods to accurately align GCP chips with VHR satellite images. In cases with seasonal differences or changed areas, edge-based algorithms are often used for matching due to the difficulty of relying solely on pixel values. However, traditional edge extraction algorithms,such as canny edge detectors, require appropriate threshold settings tailored to the spectral characteristics of satellite images. Therefore, this study utilizes deep learning-based edge information that is insensitive to the regional characteristics of satellite images for matching. Specifically,we use a pretrained pixel difference network (PiDiNet) to generate the edge maps for both satellite images and GCP chips. These edge maps are then used as input for normalized cross-correlation (NCC) and relative edge cross-correlation (RECC) to identify the peak points with the highest correlation between the two edge maps. To remove mismatched pairs and thus obtain the bias-compensated RPC, we iteratively apply the data snooping. Finally, we compare the results qualitatively and quantitatively with those obtained from traditional NCC and RECC methods. The PiDiNet network approach achieved high matching accuracy with root mean square error (RMSE) values ranging from 0.3 to 0.9 pixels. However, the PiDiNet-generated edges were thicker compared to those from the canny method, leading to slightly lower registration accuracy in some images. Nevertheless, PiDiNet consistently produced characteristic edge information, allowing for successful matching even in challenging regions. This study demonstrates that improving the robustness of edge-based registration methods can facilitate effective registration across diverse regions.

• The KIPS Transactions:PartB
• /
• v.8B no.5
• /
• pp.557-564
• /
• 2001

In general, several moving regions with different motions coexist in a block located on motion boundaries in the block-based motion estimation. In this case the motion compensation error(MCEs) are different with the moving regions. This is inclined to deteriorate the quality of motion compensated images because of the inaccurate motions estimated from the conventional mean absolute error(MAE) based matching function in which the matching error per pixel is accumulate throughout the block. In this paper, we divided a block into the regions according to their motions using the motion information of the spatio-temporally neighboring blocks and calculate the average MCF for each moving mentioned. From the simulation results, we showed the improved performance of the proposed method by comparing the results from other methods such as the full search method and the edge oriented block matching algorithm. Especially, we improved the quality of the motion compensated images of blocks on motion boundaries.