• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.43-51
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• 2014

Multi-view video including depth image is necessary to develop a new compression encoding technique for storage and transmission, because of a huge amount of data. Layered depth image is an efficient representation method of multi-view video data. This method makes a data structure that is synthesis of multi-view color and depth image. This efficient method to compress new contents is suggested to use layered depth image representation and to apply for video compression encoding by using 3D warping. This paper proposed enhanced compression method using layered depth image representation and H.264/AVC video coding technology. In experimental results, we confirmed high compression performance and good quality of reconstructed image.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.101-111
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• 1994

The human face can provide a great deal of information in regard to his/her race, age, sex, personality, feeling, psychology, mental state, health condition and ect. If we pay a close attention to the aging process, we are able to find out that there are recognizable phenomena such as eyelid drooping, cheek drooping, forehead furrowing, hair falling-out, the hair becomes gray and etc. This paper proposes that the method to estimate the age by analyzing these feature components for the facial image. Ang we also introduce the method of facial image synthesis in accordance with the cange of age. The feature components according to the change of age can be obtainec by dividing the facial image into the 3-dimensional shape of a face and the texture of a face and then analyzing the principle component respectively using 3-dimensional model. We assume the age of the facial image by comparing the extracted feature component to the facial image and synthesize the resulted image by adding or subtracting the feature component to/from the facial image. As a resurt of this simulation, we have obtained the age changed ficial image of high quality.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.85-94
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• 2023

Image halftoning is a technique for varying grayscale images into two-tone binary images. Unfortunately, the static representation of an image-half toning, wherever each pixel intensity is combined by its local neighbors only, causes missing subjective problem. Also, the existing noise causes an instability criterion. In this paper an image half-toning is represented as a dynamical system for recognizing the global representation. Also, noise is reduced based on a probabilistic model. Since image half-toning is considered as 2-D matrix with a full connected pass, this structure is recognized by the dynamical system of Cellular Neural Networks (CNNs) which is defined by its template. Bayesian Rough Sets is used in exploiting the ideal CNNs construction that synthesis its dynamic. Also, Bayesian rough sets contribute to enhance the quality of the halftone image by removing noise and discovering the effective parameters in the CNNs template. The novelty of this method lies in finding a probabilistic based technique to discover the term of CNNs template and define new learning rules for CNNs internal work. A numerical experiment is conducted on image half-toning corrupted by Gaussian noise.

• Journal of the HCI Society of Korea
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• v.2 no.2
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• pp.11-18
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• 2007

We propose a novel method to conceal fiducial markers observed in augmented scenes using patch-based texture synthesis. Despite the efficiency for simple object recognition and tracking, the markers deliver inherent obtrusiveness. They do not only reduce immersiveness, but also severely degrade usability of augmented reality. The proposed method constructs alternative images in real time to overlay markers present in the sequence of images. The global characteristics of background textures are retained and the results are more adaptive to illumination changes.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.5
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• pp.11-17
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• 1998

In this paper, the synthesis procedufe of impedance matching network is presented for broad-band microwave amplifier design, whereby amplifier operating in the octave bandwidth is designed and fabricated in detail. The transfer function of the matching netowrks is synthesized by chebyshev approximation and element values for the networks of specified topology are calculatd for various MILs and ripples. After the transistor is modeled by negative-image device model, the synthesis procedure for matching networks is applied to broad-band amplifier design which has electrical performance of about 12dB gain in 4 to 8GHz range. Experimental results obtained from the fabricated amplifier are shown to approach the electrical performance designed in the given frequency range. Construction of the impedance matching networks by transfer function synthesis is very useful method for the design of broad-band microwave amplifiers.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2002.05a
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• pp.273-277
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• 2002

This paper describes an optimal synthesis method of binary neural network(BNN) for an approximation problem of a circular region and synthetic image having four class using a newly proposed learning algorithm. Our object is to minimize the number of connections and neurons in hidden layer by using a Newly Expanded and Truncated Learning Algorithm(NETLA) based on the multilayer BNN. The synthesis method in the NETLA is based on the extension principle of Expanded and Truncated Learning (ETL) learning algorithm using the multilayer perceptron and is based on Expanded Sum of Product (ESP) as one of the boolean expression techniques. The number of the required neurons in hidden layer can be reduced and fasted for learning pattern recognition.. The superiority of this NETLA to other algorithms was proved by simulation.

• Journal of Korea Multimedia Society
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• v.11 no.6
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• pp.729-736
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• 2008

Using video synthesis to depict flowing water is useful in virtual reality, computer games, digital movies and scientific computing. This paper presents a novel algorithm for synthesizing dynamic water scenes through a sample video based on a dynamic texture model. In the paper, we treat the video sample as a 2-D texture image. In order to obtain textons, we analyze the video sample automatically based on dynamic texture model. Then, we utilize a linear dynamic system (LDS) to describe the characteristics of each texton. Using these textons, we synthesize a new video for dynamic flowing water which is prolonged and non-fuzzy in vision. Compared with other classical methods, our method was tested to demonstrate the effectiveness and efficiency with several video samples.

• Journal of Korean Neurosurgical Society
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• v.63 no.3
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• pp.386-396
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• 2020

Objective : To generate synthetic spine magnetic resonance (MR) images from spine computed tomography (CT) using generative adversarial networks (GANs), as well as to determine the similarities between synthesized and real MR images. Methods : GANs were trained to transform spine CT image slices into spine magnetic resonance T2 weighted (MRT2) axial image slices by combining adversarial loss and voxel-wise loss. Experiments were performed using 280 pairs of lumbar spine CT scans and MRT2 images. The MRT2 images were then synthesized from 15 other spine CT scans. To evaluate whether the synthetic MR images were realistic, two radiologists, two spine surgeons, and two residents blindly classified the real and synthetic MRT2 images. Two experienced radiologists then evaluated the similarities between subdivisions of the real and synthetic MRT2 images. Quantitative analysis of the synthetic MRT2 images was performed using the mean absolute error (MAE) and peak signal-to-noise ratio (PSNR). Results : The mean overall similarity of the synthetic MRT2 images evaluated by radiologists was 80.2%. In the blind classification of the real MRT2 images, the failure rate ranged from 0% to 40%. The MAE value of each image ranged from 13.75 to 34.24 pixels (mean, 21.19 pixels), and the PSNR of each image ranged from 61.96 to 68.16 dB (mean, 64.92 dB). Conclusion : This was the first study to apply GANs to synthesize spine MR images from CT images. Despite the small dataset of 280 pairs, the synthetic MR images were relatively well implemented. Synthesis of medical images using GANs is a new paradigm of artificial intelligence application in medical imaging. We expect that synthesis of MR images from spine CT images using GANs will improve the diagnostic usefulness of CT. To better inform the clinical applications of this technique, further studies are needed involving a large dataset, a variety of pathologies, and other MR sequence of the lumbar spine.

• Smart Media Journal
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• v.3 no.4
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• pp.28-34
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• 2014

Recently the depth-image-based rendering (DIBR) method is usually used in 3D image application filed. Virtual view image is created by using a known view with associated depth map to make a virtual view point which did not taken by the camera. But, disocclusion area occur because the virtual view point is created using a depth image based image 3D warping. To remove those kind of disocclusion region, many hole filling methods are proposed until now. Constant color region searching, horizontal interpolation, horizontal extrapolation, and variational inpainting techniques are proposed as a hole filling methods. But when using those hole filling method some problem occurred. The different types of annoying artifacts are appear in texture region hole filling procedure. In this paper to solve those problem, the multi-directional extrapolation method is newly proposed for efficiency of expanded hole filling performance. The proposed method is efficient when performing hole filling which complex texture background region. Consideration of directionality for hole filling method use the hole neighbor texture pixel value when estimate the hole pixel value. We can check the proposed hole filling method can more efficiently fill the hole region which generated by virtual view synthesis result.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.8
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• pp.62-70
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• 1997

In this paper, we presetn a new method to display 3-D image modelled as a sum of 2-D sliced images by expanding the concept of the conventional 2-D optical correlator based on spatial matched filtr to the 3-D region. It is hsown that a arbitrary image can be constructed by an array of the correlation-peaks between pixel-to-pixel and propose the systhesis precedure of 3-D spatial-matched-fjilter using fresnel diffraction equation to display 3-D image in space. It is also shown that the quantization problem is severe when the systehsised filter function is displayed on the conventional LC-SLM. To overcome this problem, anonlinear quantizaton method using the sigmoid function is suggested, and this method can reduce the bias and the loss of high spatial-frequency information, and improve the diffraction efficiency. Finally, the suggested method is tested by computer simulation and then approved by some optical experiments with the conventional LC-SLM.