• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.1-11
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• 2023

In this paper, instead of using recurrent neural network, we compare a classification performance of time series imaging algorithms using convolution neural network. There are traditional algorithms that imaging time series data (e.g. GAF(Gramian Angular Field), MTF(Markov Transition Field), RP(Recurrence Plot)) in TSC(Time Series Classification) community. Furthermore, we compare STFT(Short Time Fourier Transform) algorithm that can acquire spectrogram that visualize feature of voice data. We experiment CNN's performance by adjusting hyper parameters of imaging algorithms. When evaluate with GunPoint dataset in UCR archive, STFT(Short-Time Fourier transform) has higher accuracy than other algorithms. GAF has 98~99% accuracy either, but there is a disadvantage that size of image is massive.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.157-160
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• 1996

In this paper, reconstruction algorithms of spiral scan imaging which has been used for ultra fast magnetic resonance imaging have been reviewed, and some simulation results using two different algorithms are reported. Since the trajectory of the spiral scan in k-space is the spiral, reconstruction of the spiral scan is not as straight forward as that used in Fourier imaging technique where the sampling points are usually on the rectangular grids. Originally the reconstruction of the spiral scan imaging was based on the convolution backprojection algorithm modified with a shift term, however, some other reconstruction techniques have also been tried by remapping sampling points from spiral trajectory to Cartesian grids. Some experimental aspects of MR spiral scan imaging will also be addressed.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1747-1753
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• 2022

Compton imaging is the main method for locating radioactive hot spots emitting high-energy gamma-ray photons. In particular, this imaging method is crucial when the photon energy is too high for coded-mask aperture imaging methods to be effective or when a large field of view is required. Reconstruction of the photon source requires advanced Compton event processing algorithms to determine the exact position of the source. In this study, we introduce a novel method based on a Deep Learning algorithm with a Convolutional Neural Network (CNN) to perform Compton imaging. This algorithm is trained on simulated data and tested on real data acquired with Caliste, a single planar CdTe pixelated detector. We show that performance in terms of source location accuracy is equivalent to state-of-the-art algorithms, while computation time is significantly reduced and sensitivity is improved by a factor of ~5 in the Caliste configuration.

• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.229-251
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• 2021

Arteriosclerosis is the leading cause of stroke, with a fatality rate surpassing that of ischemic heart disease. High-resolution vessel wall magnetic resonance imaging is generally recognized as a non-invasive and panoramic method for the evaluation of arterial plaque; however, this method requires improved signal-to-noise ratio and scanning speed. Recent advances in high-density head and neck coil arrays are characterized by broad coverage, multiple channels, and closefitting designs. This review analyzes fast magnetic resonance imaging from the perspective of accelerated algorithms for vessel wall imaging and demonstrates the need for effective algorithms for signal acquisition using advanced radiofrequency system. We summarize different phased-array structures under various experimental objectives and equipment conditions, introduce current research results, and propose prospective research studies in the future.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.2
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• pp.97-103
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• 2017

Thermal imaging is mainly used in military equipment required for night observation. In particular, technologies of uncooled thermal imaging detectors are being developed as applied to low-cost night observation system. Many system integrators require different specifications of the uncooled thermal imaging camera but their development time is short. In this approach, EOSYSTEM has developed a small size, TEC-less uncooled thermal imaging camera module with $32{\times}32mm$ size and low power consumption. Both domestic detector and import detector are applied to the EOSYSTEM's thermal imaging camera module. The camera module contains efficient infrared image processing algorithms including : Temperature compensation non-uniformity correction, Bad/Dead pixel replacement, Column noise removal, Contrast/Edge enhancement algorithms providing stable and low residual non-uniformity infrared image.

• Journal of the Korean Data and Information Science Society
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• v.15 no.3
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• pp.695-706
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• 2004

The use of wavelets in three-dimensional imaging is reviewed with an example. The insufficiencies of direct two-dimensional processing is showed as a major motivating factor behind using wavelets for three-dimensional imaging. Different wavelet algorithms are used, and these are compared with the direct two-dimensional approach as well as with each other.

• ETRI Journal
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• v.25 no.3
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• pp.156-170
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• 2003

Gamut compression algorithms have traditionally been defined functionally and then tested with deductive methods, e.g., psychophysical experiments. Our study offers an alternative, an inductive method, in which observers judge image colors to represent the original images more accurately. We developed a computer-controlled interactive tool that modifies the color appearance of pictorial images displayed on a monitor. In experiments, observers used the tool to alter color pixels according to the region of color space to which they belonged. We created three different gamut compression algorithms based on the observer experimental data. Observer groups evaluated the performance of the newly-developed algorithms, existing gamut compression algorithms, and an image based on the average observers' results from experiments in this study. The study of gamut extension is unlike the study of gamut compression in that it mainly deals with the degree of image pleasantness as judged by observers. The results of the gamut extension experiments in this study not only make available worthwhile data but also suggest a methodology for using the observer experimental tool for future gamut extension research.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.4
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• pp.467-475
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• 2016

Ultrasonic propagation imaging (UPI) has shown great potential for detection of impairments in complex structures and can be used in wide range of non-destructive evaluation and structural health monitoring applications. The software implementation of such algorithms showed a tendency in time-consumption with increment in scan area because the processor shares its resources with a number of programs running at the same time. This issue was addressed by using field programmable gate arrays (FPGA) that is a dedicated processing solution and used for high speed signal processing algorithms. For this purpose, we need an independent and flexible block of logic which can be used with continuously evolvable hardware based on FPGA. In this paper, we developed an FPGA-based ultrasonic propagation imaging system, where FPGA functions for both data acquisition system and real-time ultrasonic signal processing. The developed UPI system using FPGA board provides better cost-effectiveness and resolution than digitizers, and much faster signal processing time than CPU which was tested using basic ultrasonic propagation algorithms such as ultrasonic wave propagation imaging and multi-directional adjacent wave subtraction. Finally, a comparison of results for processing time between a CPU-based UPI system and the novel FPGA-based system were presented to justify the objective of this research.

• The Journal of Korea Robotics Society
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• v.10 no.3
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• pp.146-153
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• 2015

In order to contain as much information as possible in a single image, a wide FOV(Field-Of-View) imaging system is required. The catadioptric imaging system with hyperbolic cylinder mirror can acquire over 180 degree horizontal FOV realtime panorama image by using a conventional camera. Because the hyperbolic cylinder mirror has a curved surface in horizontal axis, the original image acquired from the imaging system has the geometrical distortion, which requires the image processing algorithm for reconstruction. In this paper, the image reconstruction algorithms for two cases are studied: (1) to obtain an image with uniform angular resolution and (2) to obtain horizontally rectilinear image. The image acquisition model of the hyperbolic cylinder mirror imaging system is analyzed by the geometrical optics and the image reconstruction algorithms are proposed based on the image acquisition model. To show the validity of the proposed algorithms, experiments are carried out and presented in this paper. The experimental results show that the reconstructed images have a uniform angular resolution and a rectilinear form in horizontal axis, which are natural to human.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.243-250
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• 1998

Reconstruction aspects of spiral scan imaging for ultra fast magnetic resonance imagine(MRI) have been investigated with polar and rectangular coordinates-based reconstruction. For the reconstruction of the spiral scan imaging, acquired data in spiral trjectory should be converted to polar or rectangular grids, where interpolation techniques are used. Various reconstruction algorithms for spiral scan imaging are tested, and reconstructed image qualities are compared with computed phantom. An improved reconstruction algorithm with dc-offset correction in projection domain is proposed, which provides the best reconstructed image quality from the simulation. Image artifact with existing algorithms is completely removed with the proposed method.