• Korean Journal of Remote Sensing
• /
• v.27 no.2
• /
• pp.141-150
• /
• 2011

Precise image-to-image registration is required to process multi-sensor data together. The purpose of this paper is to develop an algorithm that register between high-resolution optical and SAR images using linear features. As a pre-processing step, initial alignment was fulfilled using manually selected tie points to remove any dislocations caused by scale difference, rotation, and translation of images. Canny edge operator was applied to both images to extract linear features. These features were used to design a cost function that finds matching points based on their similarity. Outliers having larger geometric differences than general matching points were eliminated. The remaining points were used to construct a new transformation model, which was combined the piecewise linear function with the global affine transformation, and applied to increase the accuracy of geometric correction.

• Journal of Sensor Science and Technology
• /
• v.28 no.3
• /
• pp.182-186
• /
• 2019

When a camera is employed for 3D sensing, accurate camera calibration is vital as it is a prerequisite for the subsequent steps of the sensing process. Camera calibration is usually performed by complex mathematical modeling and geometric analysis. On the other contrary, data learning using an artificial neural network can establish a transformation relation between the 3D space and the 2D camera image without explicit camera modeling. However, a neural network requires a large amount of accurate data for its learning. A significantly large amount of time and work using a precise system setup is needed to collect extensive data accurately in practice. In this study, we propose a two-step neural calibration method that is effective when only a small amount of learning data is available. In the first step, the camera projection transformation matrix is determined using the limited available data. In the second step, the transformation matrix is used for generating a large amount of synthetic data, and the neural network is trained using the generated data. Results of simulation study have shown that the proposed method as valid and effective.

• Korean Journal of Remote Sensing
• /
• v.40 no.3
• /
• pp.257-268
• /
• 2024

Drone-mounted hyperspectral sensors (DHSs) have revolutionized remote sensing in agriculture by offering a cost-effective and flexible platform for high-resolution spectral data acquisition. Their ability to capture data at low altitudes minimizes atmospheric interference, enhancing their utility in agricultural monitoring and management. This study focused on addressing the challenges of radiometric and geometric distortions in preprocessing drone-acquired hyperspectral data. Radiometric correction, using the empirical line method (ELM) and spectral reference panels, effectively removed sensor noise and variations in solar irradiance, resulting in accurate surface reflectance values. Notably, the ELM correction improved reflectance for measured reference panels by 5-55%, resulting in a more uniform spectral profile across wavelengths, further validated by high correlations (0.97-0.99), despite minor deviations observed at specific wavelengths for some reflectors. Geometric correction, utilizing a rubber sheet transformation with ground control points, successfully rectified distortions caused by sensor orientation and flight path variations, ensuring accurate spatial representation within the image. The effectiveness of geometric correction was assessed using root mean square error(RMSE) analysis, revealing minimal errors in both east-west(0.00 to 0.081 m) and north-south directions(0.00 to 0.076 m).The overall position RMSE of 0.031 meters across 100 points demonstrates high geometric accuracy, exceeding industry standards. Additionally, image mosaicking was performed to create a comprehensive representation of the study area. These results demonstrate the effectiveness of the applied preprocessing techniques and highlight the potential of DHSs for precise crop health monitoring and management in smart agriculture. However, further research is needed to address challenges related to data dimensionality, sensor calibration, and reference data availability, as well as exploring alternative correction methods and evaluating their performance in diverse environmental conditions to enhance the robustness and applicability of hyperspectral data processing in agriculture.

• Journal of Educational Research in Mathematics
• /
• v.25 no.4
• /
• pp.499-524
• /
• 2015

In the present study, we propose four participating $8^{th}$ grade students' genetic decomposition of congruent transformation and investigate the role of their dragging activities while understanding the concept of congruent transformation in GSP(Geometer's Sketchpad). The students began to use two major schema, 'single-point movement' and 'identification of transformation' simultaneously in their transformation activities, but they were inclined to rely on the single-point movement schema when dealing with relatively difficult tasks. Through dragging activities, they could expand the domain and range of transformation to every point on a plane, not confined to relevant geometric figures. Dragging activities also helped the students recognize the role of a vector, a center of rotation, and an axis of symmetry.

• Journal of Ocean Engineering and Technology
• /
• v.13 no.3 s.33
• /
• pp.12-20
• /
• 1999

In this paper, method for mapping a three-dimensional shape into the two-dimensional plane will be introduced. This method is referred to geometric modelling and means a transformation between the flat sheet and final surface. The initial blank shape represents the original configuration of the final shape formed into three dimensional surface. The initial constant constant area mapping hypothesis was used in this paper. This technique will be applied to the basic data for an interactive computer design capable of dealing with typical stamping process, including deep parts and complex shapes.

• Bulletin of the Korean Chemical Society
• /
• v.28 no.10
• /
• pp.1705-1708
• /
• 2007

Geometric manipulation of molecules is an essential elementary component in computational modeling programs for molecular structure, stability, dynamics, and design. The computational complexity of transformation of internal coordinates to Cartesian coordinates was discussed before.1 The use of rotation matrices was found to be slightly more efficient than that of quaternion although quaternion operators have been widely advertised for rotational operations, especially in molecular dynamics simulations of liquids where the orientation is a dynamical variable.2 The discussion on computational efficiency is extended here to a more general case in which bond angles and sidechain torsion angles are allowed to vary. The algorithm of Thompson3 is derived again in terms of quaternions as well as rotation matrices, and an algorithm with optimal efficiency is described. The algorithm based on rotation matrices is again found to be slightly more efficient than that based on quaternions.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.4 no.3
• /
• pp.39-47
• /
• 1995

This paper suggests generalize mathematica mode for the benefit of volumetric error analysis of a multi-axis machine tool machining a sculptured surfaces. The volumetric error, in this paper, is defined as a three dimensional error at the cutting point, which is caused by the geometric errors and the kinematic errors of each axis and alignment errors of the cutting tool. The actual cutting position is analyzed based on the form shaping model including a geometric error of the moving carriage, where a form shaping model is derived from the homogeneous transformation matrix. Then the volumetric error is obtained by calculating the position difference between the actual cutting position and the ideal one calculated from a Nonuniform Rational B-Spline named as NURES. The simulation study shows the effectiveness for predicting the behavior of machining error and for the method of error compensation.

• 연구논문집
• /
• s.23
• /
• pp.45-56
• /
• 1993

In order to acquire more comprehensive understanding of textile composites, the processing-microstructure-performance relationships for a variety of material systems, reinforcing schemes and processing technologies should be established. In this paper, emphasis is placed on the integrated analysis of three-dimensional (3-D) 2-step braided composites. The analysis includes the geometric model of unit cells, identification of key process parameters and processing windows due to limiting geometries of yarn jamming, and prediction of elastic constants of the composite. The coordinate transformation and averaging of stiffness and compliance constants are utilized in the prediction of elastic constants. Since there are several types of unit cells in the thickness and width directions of the composites, characterization of mechanical properties is based upon the macro-cell, which occupies the entire cross-section and the unit pitch length of the sample. The performance map demonstrates that a wide range of elastic properties can be achieved by varying the geometric and process parameters.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2003.11a
• /
• pp.23-29
• /
• 2003

Detection in remotely sensed images can be conducted spatially, spectrally or both [2]. If the images have high spatial resolution, materials can be detected by using spatial and spectral information, unless we can't see the object embedded in a pixel. In this paper, we intend to solve the limit of spatial resolution by using the hyperspectral image which has high spectral resolution. Therefore, the Linear Spectral Mixing(LSM) Model which is sub-pixel detection algorithm is used to solve this problem. To find class Endmembers, we applied Geometric Model with MNF(Minimum Noise Fraction) transformation. From the result of sub-pixel detection algorithm, we can see the detection of water is satisfied and the object shape cannot be extracted but the possibility of material existence can be identified.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.3 no.4
• /
• pp.7-12
• /
• 2004

Inspection and analysis are essential process to determine whether a completed product is in given specification or not. Analysis of products with very complicated shape is difficult to carry out direct comparison between inspected coordinate and designed coordinates. So process called as matching or registrations is needed to solve this problem. By defining error between two coordinates and minimizing the error, registration is done. Registration consists of translation, rotation and scale transformations. Error must be defined to express feature of inspected product. In this paper, registration algorithm is developed to determine pose of sub-frame at assembly with body of automobile by defining error between two coordinates considering geometric feature of sub-frame.