• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.450-455
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• 2009

Amplitude-only logarithmic Radon transform (ALR transform) for pattern matching is proposed. This method provides robustness for object translation, scaling, and rotation. An ALR image is invariant even if objects are translated in a picture. For the object scaling and rotation, the ALR image is merely translated. The objects are identified using a phase-only matched filter to the ALR image. The ratio of size, the difference of rotation angle, and the position between the two objects are detected. Our pattern matching procedure is described, herein, and its simulation is executed. We compare matching scores with the Fourier-Mellin transform, and the general phase-only matched filter.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.76-79
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• 2009

This paper investigates the performance of a vehicular rear-view camera through quantifying the image quality based on several objective criteria from the ISO (International Organization for Standardization). In addition, various experimental environments are defined considering the conditions under which a rear-view camera may need to operate. The process for evaluating the performance of a rear-view camera is composed of five objective criteria: noise test, resolution test, OECF (opto-electronic conversion function) test, color characterization test, and pincushion and barrel distortion tests. The proposed image quality quantification method then expresses the results of each test as a single value, allowing easy evaluation. In experiments, the performance evaluation results are analyzed and compared with those for a regular digital camera.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.355-359
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• 2009

In this paper, we describe self-training super-resolution. Our approach is based on example based algorithms. Example based algorithms need training images, and selection of those changes the result of the algorithm. Consequently it is important to choose training images. We propose self-training based super-resolution algorithm which use an input image itself as a training image. It seems like other example based super-resolution methods, but we consider training phase as the step to collect primitive information of the input image. And some artifacts along the edge are visible in applying example based algorithms. We reduce those artifacts giving weights in consideration of the edge direction. We demonstrate the performance of our approach is reasonable several synthetic images and real images.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.516-519
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• 2009

In the printer and the facsimile communication, digital halftoning is extremely important technologies. Error diffusion method is applied easy for color image halftoning. But the problem in error diffusion method is that a quite unrelated color has been generated though it is necessary to express the area of the grayscale in the black and white when the image that there is an area of the grayscale on a part of the color image is processed. The halftoning was assumed to be a combinational optimization problem to solve this problem, and the method of using SA (Simulated Annealing) was proposed. However, new problem existed because the processing time was a great amount compared with error diffusion method. Then, we propose the new error diffusion method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.529-534
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• 2009

This paper reports a non-photorealistic rendering method for creating stream pattern from an input image. Our method extracts potential stream pattern in the given image. The proposed approach uses a shock filter based on a partial difference equation(PDE) which is implemented by applying a selective dilation and erosion processes. However, unlike the traditional first order solution to the PDE, we employ a second order scheme and compensate for the undesired diffusive effects caused by a viscosity form. The selection of dilation or erosion for a pixel is based on an edge detector computed from a structure tensor. By adding noises on to the input image, our method also can generate stream pattern even if there is less texture in some area. The experimental results show that the stream pattern is extracted very well.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.678-683
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• 2009

A lot of researches [1] have been conducted on digital watermark embedding in brightness. A prerequisite for the digital watermark is that the image quality does not change even if the volume of the embedded information increases. Generally, the noise on complex images is perceived than the noise on fiat images. Thus, we present a method for watermarking an image by embedding complex areas by priority. The proposed method has achieved higher image quality of digital watermarking compared to other method that do not take into consideration the complexity of blocks, although the PSNR of the proposed method is lower than for a method not based on block complexity.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.174-177
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• 2009

In object tracking, the template matching methods have been developed and frequently used. It is fast enough, but not robust to an object with the variation of size and shape. In order to overcome the limitation of the template matching method, this paper proposes a template update technique. After finding an object position using the correlation-based adaptive predictive search, the proposed method selects blocks which contain object's boundary. It estimates the motion of boundary using block matching, and then updates template. We applied it to IR image sequences including an approaching object. From the experimental results, the proposed method showed successful performance to track object.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06b
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• pp.23-28
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• 1996

Model-based coding is one of several approaches to very low bit rate image coding and it can be used in many applications such as image creation and virtual reality. However, its analysis and synthesis processes remain difficult, especially in the sense that the resulting synthesized image reveals some degradation in detailed facial components such as furrows around eyes and mouth. To solve the problem, a large number of methods have been proposed and the texture update method is one of them. In this paper, we investigate texture synthesis for model-based coding. In the update process of the proposed texture synthesis algorithm, texture information is stored in a memory and the decoder reuses it. With this method, the transmission bit rate for texture data can be reduced compared with the conventional method updating texture periodically.

• Journal of Broadcast Engineering
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• v.1 no.1
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• pp.22-28
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• 1996

In color indexed images using the palette, the corrupted indices cause serious quality degradation in the reconstructed images at a receiver. In this paper, using the human visual characteristics of color perception, we propose the color image palette minimizing the quality degradation and the reconstruction error. We define the new measure to compare the performance of palette .construction algorithms and show the effectiveness of the proposed method under the bit error condition by computer simulation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.11a
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• pp.52-53
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• 2012

Belief propagation (BP) is a commonly used global energy minimization algorithm for solving stereo matching problem in 3D reconstruction. However, it requires large memory bandwidth and data size. In this paper, we propose a novel memory-efficient algorithm of BP in stereo matching on the Graphics Processing Units (GPU). The data size and transfer bandwidth are significantly reduced by storing only a part of the whole message. In order to maintain the accuracy of the matching result, the local messages are reconstructed using shared memory available in GPU. Experimental result shows that there is almost an order of reduction in the global memory consumption, and 21 to 46% saving in memory bandwidth when compared to the conventional algorithm. The implementation result on a recent GPU shows that we can obtain 22.8 times speedup in execution time compared to the execution on CPU.