• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.434-442
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• 2008

The parallel beam SPECT acquires projection data by using parallel hole collimators in conjunction with photon detectors. Those projection data of the parallel beam SPECT are, however, contaminated by the distance dependent blurring because of the inaccuracy of the point response function of the collimator that is used to define the range of directions where photons can be detected. Thus an efficient aperture correction is required. In this paper we propose a distance dependent backprojection method to overcome the time limitation of iterative aperture correction methods and the performance limitation of Fourier-Distance Relation based method. The proposed method achieves aperture correction and fast image reconstruction by replacing the distance independent backprojection of the direct image reconstruction with the distance dependent one. We conducted several simulations to compare the performance of the proposed method with that of the conventional Fourier-Distance Relation based method. The simulation result shows that the proposed method outperforms the Fourier-Distance Relation based method in spatial resolution and robustness against noise.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.4
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• pp.685-692
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• 2024

In this paper, we propose a new CNN model to improve the recognition performance of command voice signals. This method obtains a spectrogram image after performing a short-time Fourier transform (STFT) of the input signal and improves command recognition performance through supervised learning using a CNN model. After Fourier transforming the input signal for each short-time section, a spectrogram image is obtained and multi-classification learning is performed using a CNN deep learning model. This effectively classifies commands by converting the time domain voice signal to the frequency domain to express the characteristics well and performing deep learning training using the spectrogram image for the conversion parameters. To verify the performance of the speech recognition system proposed in this study, a simulation program using Tensorflow and Keras libraries was created and a simulation experiment was performed. As a result of the experiment, it was confirmed that an accuracy of 92.5% could be obtained using the proposed deep learning algorithm.

• Journal of Astronomy and Space Sciences
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• v.41 no.3
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• pp.159-170
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• 2024

A method for resident space object detection in video stream processing using a set of matched filters has been proposed. Matched filters are constructed based on the connection between the Fourier spectrum shape of the difference frame and the magnitude of the linear velocity projection onto the observation plane. Experimental data were obtained using the mobile optical surveillance system for low-orbit space objects. The detection problem in testing mode was solved for raw video data with intensity signals from three satellites: KORONAS-FOTON, CUSAT 2/FALCON 9, and GENESIS-1. Difference frames of video data with the AQUA satellite pass were used to construct matched filters. The satellites were automatically detected at points where the difference in the value of their linear velocity projection and the reference satellite was close in value. An initial approximation of the satellites slant range vector and position vector has been obtained based on the values of linear velocity projection onto the frame plane. It has been established that the difference in the inclination angle between the detected satellite intensity signal Fourier image and the reference satellite mask corresponds to the difference in the inclinations of these objects. The proposed method allows for detecting and estimating the initial approximation of the slant range and position vector of artificial and natural space objects, such as satellites, debris, and asteroids.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.260-262
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• 2003

New Image registration techniques are developed for determining geometric distortions between two images of the same scene. First, the properties of the Fourier transform of a two dimensional function under the affine transformation are given. As a result, techniques for the estimation of the coefficients of the distortion model using the spectral frequency information are developed. Image registration can be achieved by applying the fast Fourier transform (FFT) technique for cross correlation of misregistered imagery to determine spatial distances. The correlation results may be rather broad, making detection of the peak difficult, what can be suppressed by enhancing cross-correlation technique. Yield greatly improves the delectability and high precision of image misregistration.

• Bulletin of the Korean Mathematical Society
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• v.22 no.2
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• pp.87-88
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• 1985

• Journal of the Korean Mathematical Society
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• v.11 no.1
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• pp.25-28
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• 1974

• Archives of design research
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• v.19 no.2 s.64
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• pp.313-322
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• 2006

In this paper, we introduce 'Contents Based Image Retrieval' which helps a user find the images he or she needs more easily and reconfigures the images automatically. With this system, we try to realize the language of (motion) picture, that is, the Montage from the viewpoint of the user. The Real-time Montage System introduced in this paper uses 'Discrete Fourier Transform'. Through this, the user can find the feature of the image selected and compare the analogousness with the image in the database. This kind of system leads to the user's speedy and effective retrieving, Also, we can acquire the movement image of the user by Camera Tracking in Real-time. The movement image acquired is to be reconfigured automatically with the image of the user. In this way, we can get an easy and speedy image reconfiguration which sets to the user's intention. This system is a New Media Design tool(entertainment) which induces a user enjoy participating in it. In this system, Thus, the user is not just a passive consumer of one-way image channels but an active subject of image reproduction in this system. It is expected to be a foundation for a new style of user-centered movie (media based entertainment).

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.1112-1119
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• 1999

Digital watermarking is to embed imperceptible mark into image, video, audio and text data to prevent the illegal copy of multimedia data, arbitrary modification, and also illegal sales of the copes without agreement of copyright ownership. The DCT(discrete Cosine Transforms) transforms of original image is conducted in this research and these DCT coefficients are expanded by Fourier series expansion algorithm. In order to embed the imperceptible and robust watermark, the Fourier coefficients(lower frequency coefficients) can be calculated using sine and cosine function which have a complete orthogonal basis function, and the watermark is embedded into these coefficients, In the experiment, we can show robustness with respect to image distortion such as JPEG compression, bluring and adding uniform noise. The correlation coefficient are in the range from 0.5467 to 0.9507.

• Current Optics and Photonics
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• v.2 no.2
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• pp.165-171
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• 2018

Fourier ptychographic microscopy (FPM) is a recently proposed computational imaging method that achieves both high resolution (HR) and wide field of view. In the FPM framework, a series of low-resolution (LR) images at different illumination angles is used for high-resolution image reconstruction. On the basis of previous research, image noise can significantly degrade the FPM reconstruction result. Since the captured LR images contain a lot of dark-field images with low signal-to-noise ratio, it is very important to apply a noise-reduction process to the FPM raw dataset. However, the thresholding method commonly used for the FPM data preprocessing cannot separate signals from background noise effectively. In this work, we propose an improved thresholding method that provides a reliable background-noise threshold for noise reduction. Experimental results show that the proposed method is more efficient and robust than the conventional thresholding method.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1013-1020
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• 2005

This paper presents an effective and robust leaf image retrieval system based on shape feature. Specifically, we propose an improved MPP algorithm for more effective representation of leaf images and show a new dynamic matching algorithm that basically revises the Nearest Neighbor search to reduce the matching time. In particular, both leaf shape and leaf arrangement can be sketched in the query for better accuracy and efficiency. In the experiment, we compare our proposed method with other methods including Centroid Contour Distance(CCD), Fourier Descriptor, Curvature Scale Space Descriptor(CSSD), Moment Invariants, and MPP. Experimental results on one thousand leaf images show that our approach achieves a better performance than other methods.