• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.41 no.6 s.324
• /
• pp.79-86
• /
• 2004

In the integration of Sommerfeld type for space domain Green's function, a accurate closed-from Green's function method provides more exact solution than the typical complex image method and two-level method. The accurate closed-form Green's function method is applied to obtain the space domain Green's functions of planar structures with general sources. Please put the abstract of paper here.

• Journal of Digital Contents Society
• /
• v.11 no.1
• /
• pp.73-78
• /
• 2010

This study attempted to examine whether the propeller diffusion weighted image method may remove magnetic susceptibility artifacts caused by metallic materials. A comparison of occurrence rates of magnetic susceptibility artifacts in the four regions, both temporal lobes, pons, and orbit, between b = 0 and b = 1,000 s/mm2 images was made after obtaining echo-planar diffusion weighted image, propeller diffusion weighted image, and ADC map images, respectively, from a total of 20 patients who had MRI shots taken of their brain and were found to be with retained metallic foreign bodies within their teeth using a 3.0T MR scanner. In the case of echo-planar diffusion weighted image technique, the presence of metallic materials may bring in some limits on accurate diagnosis due to magnetic susceptibility artifacts, while the propeller diffusion weighted image technique where magnetic susceptibility artifacts decrease is expected to be more useful in ensuring accurate diagnosis in the clinical context.

• Current Optics and Photonics
• /
• v.6 no.3
• /
• pp.260-269
• /
• 2022

Segmented planar imaging detector for electro-optical reconnaissance (SPIDER) is an emerging technology for optical imaging. However, this novel detection approach is faced with degraded imaging quality. In this study, a 6 × 6 planar waveguide is used after each lenslet to expand the field of view. The imaging principles of field-plane waveguide structures are described in detail. The local multiple-sampling simulation mode is adopted to process the simulation of the improved imaging system. A novel image-reconstruction algorithm based on deep learning is proposed, which can effectively address the defects in imaging quality that arise during image reconstruction. The proposed algorithm is compared to a conventional algorithm to verify its better reconstruction results. The comparison of different scenarios confirms the suitability of the algorithm to the system in this paper.

• The Korean Journal of Nuclear Medicine Technology
• /
• v.28 no.1
• /
• pp.57-69
• /
• 2024

Purpose: Quantitative analysis through count measurement in nuclear medicine planar images is limited by analysis techniques that are useful for obtaining various clinical information or by organ overlap or artifacts in actual clinical practice. On the other hand, the use of SPECT tomography images is quantitative analysis using volume rather than planar, which is not only free from problems such as projection overlap, but also has excellent quantitative accuracy. In the use of developing SPECT quantitative analysis technology, this study aims to compare the accuracy of quantitative analysis between ROI of the conventional planar images and VOI of the SPECT tomographic images in evaluating the count change happened by the volume change of the source. Materials and Methods: A ^99mTcO₄^- source(200.17 MBq) was filled with sterilized water in the syringe to create a phantom with an inner diameter volume of 60 cc, and a planar image and a SPECT image were obtained by reducing the volume by 15 cc (25%) respectively. ROI and VOI(threshold: 1~45%, 5% interval) were set for each image obtained to estimate true count and measure the total count, and compared with the preseted volumetric change rate(%). Results: When volume changes of 25%, 50%, and 75% occurred in the initial volume of 60 cc(100%) of the phantom, the average count changes of the measured planar image were 26.8%, 53.2%, 77.5%, and the average count changes of the SPECT image were 24.4%, 50.9%, and 76.8%. In this case, the VOI size(cm³) set showed an average change rate of 25.4%, 51.1%, and 76.6%. The highest threshold value for the accuracy of radioactive concentration by VOI size (average error -1.03%) was 35%, and the VOI size of the same threshold had an error of -17.1% on average compared to the actual volume. Conclusion: On average, the count-based volumetric change rate in nuclear medicine images was able to track changes more accurately using VOI than ROI, but there was no significant difference with relatively similar value. However, the accuracy of radioactive concentration according to individual VOI sizes did not match, but it is considered that a relatively accurate quantitative analysis can be expected when the size of VOI is set smaller than the actual volume.

• Proceedings of the KIEE Conference
• /
• 1990.07a
• /
• pp.546-549
• /
• 1990

This study introduces the three-dimensional information about moving objects. Relative motion between textured objects and observer generates a time varying optic array at the image, from which image motion of contours can be extracted. Closed-form solutions are proposed for the structure and motion of planar and curved surface patches. The analytic solution for curved surface patches combines the transformation of Longuet-Higgins with the planar surface solution of Subbarao and Waxman. Ovoid patches are shown to construct a unique transform angle. Thus, ovoid patches almost always yield a unique 3D interpretation.

• Journal of IKEEE
• /
• v.21 no.4
• /
• pp.412-415
• /
• 2017

In this paper, we propose a multi license plate recognition system using high resolution $360^{\circ}$ omnidirectional IP camera. The proposed system consists of a planar division part of $360^{\circ}$ circular image and a multi license plate recognition part. The planar division part of the $360^{\circ}$ circular image are divided into a planar image with enhanced image quality through processes such as circular image acquisition, circular image segmentation, conversion to plane image, pixel correction using color interpolation, color correction and edge correction in a high resolution $360^{\circ}$ omnidirectional IP Camera. Multi license plate recognition part is through the multi-plate extraction candidate region, a multi-plate candidate area normalized and restore, multiple license plate number, character recognition using a neural network in the process of recognizing a multi-planar imaging plates. In order to evaluate the multi license plate recognition system using the proposed high resolution $360^{\circ}$ omnidirectional IP camera, we experimented with a specialist in the operation of intelligent parking control system, and 97.8% of high plate recognition rate was confirmed.

• Journal of Korea Multimedia Society
• /
• v.25 no.7
• /
• pp.912-921
• /
• 2022

Autonomous vehicles equipped with cameras, such as robots, fork lifts, or cars, can be found frequently in industry sites or usual life. Those cameras show planar motion because the vehicles usually move on a plane. Sometimes the cameras in fork lifts moves vertically. The cameras under planar and vertical motion provides useful properties for horizontal or vertical lines that can be found easily and frequently in our daily life. In this paper, some useful back-projection properties are suggested, which can be applied to horizontal or vertical line images captured by a camera under planar and vertical motion. The line images are back-projected onto a virtual plane that is parallel to the planar motion plane and has the same orientation at the camera coordinate system regardless of camera motion. The back-projected lines on the virtual plane provide useful information for the world lines corresponding to the back-projected lines, such as line direction, angle between two horizontal lines, length ratio of two horizontal lines, and vertical line direction. Through experiments with simple plane polygons, we found that the back-projection properties were useful for estimating correctly the direction and the angle for horizontal and vertical lines.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.10a
• /
• pp.255-262
• /
• 1998

This paper presents a translation, rotation and scale invariant methodology for the recognition of closed planar shape images using the bispectrum of a contour sequence and the learning vector quantization(LVQ) neural classifier. The contour sequences obtained from the closed planar images represent the Euclidean distance between the centroid and all boundary pixels of the shape, and are related to the overall shape of the images. The higher order spectra based on third order cumulants is applied to tihs contour sample to extract fifteen bispectral feature vectors for each planar image. There feature vector, which are invariant to shape translation, rotation and scale transformation, can be used to represent two0dimensional planar images and are fed into a neural network classifier. The LVQ architecture is chosen as a neural classifier because the network is easy and fast to train, the structure is relatively simple. The experimental recognition processes with eight different hapes of aircraft images are presented to illustrate the high performance of this proposed method even the target images are significantly corrupted by noise.

• Journal of Korea Game Society
• /
• v.18 no.5
• /
• pp.5-14
• /
• 2018

A lot of research has been done on image recognition technique for planar images and the performance has also been improved. However, it is difficult to recognize objects in spherical panoramic images or images in special form which are given in various environments because of the spherical distortion given in different form from the planar case. In this paper, we show that the neural network recognition approach can be used for object recognition in spherical image and suggest a method of using cubemap transform in order to increase recognition accuracy in spherical image.

• Ocean and Polar Research
• /
• v.35 no.3
• /
• pp.229-237
• /
• 2013

We measured two-dimensional (2-D) oxygen distribution in the surface sediment layer of intertidal sediment using a simple and inexpensive planar oxygen optode, which is based on a color ratiometric image approach. The recorded emission intensity of red color luminophore light significantly changed with oxygen concentration by $O_2$ quenching of platinum(II)octaethylporphyrin (PtOEP). The ratios between the intensity of red and green emissions with oxygen concentration variation demonstrated the Stern-Volmer relationship. The 2-D oxygen distribution image showed microtopographic structure, diffusivity boundary layer and burrow in surface sediment layer. The oxygen penetration depth (OPD) was about 2 mm and the one-dimensional vertical diffusive oxygen uptake (DOU) was 12.6 mmol $m^{-2}d^{-1}$ in the undisturbed surface sediment layer. However, those were enhanced near burrow by benthic fauna, and the OPD was two times deeper and DOU was increased by 34%. The simple and inexpensive oxygen planar optode has great application potential in the study of oxygen dynamics with high spatiotemporal resolution, in benthic boundary layers.