• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.532-535
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• 2005

These days, many image processing techniques have been studied for effective image compression. Among those, 2D image filtering is widely used for 2D image processing. The 2D image filtering can be implemented by performing ID linear filtering separately in the direction of horizontal and vertical. Efficiency of image compression depends on what filtering method is used. Generally, circular convolution is widely used in the 2D image filtering for image processing. However it doesn't consider correlations at the region of image boundary, therefore filtering can not be performed effectively. To solve this problem. I proposed new convolution technique using Symmetric-Mirroring convolution, satisfying the 'alias-free' and 'error-free' requirement in the reconstructed image. This method could provide more effective performance than former compression methods. Because it used very high correlative data when performed at the boundary region. In this paper, pre-processing filtering in H.264 codec was adopted to analyze efficiency of proposed filtering technique, and the simulator developed by Matlab language was used to examine the performance of the proposed method.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.07a
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• pp.319-322
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• 2001

The proposed system was composed of pre-processor which was executing binary/high-pass filtering and post-processor which ranged from statistic data to prediction. In post-processor work, step one was filter process of image, step two was image recognition, and step three was destruction degree/time prediction. After these processing, we could predict image of the last destruction timestamp. This research was produced variation value according to growth of tree pattern. This result showed improved correction, when this research was applied image Processing. Pre-processing step of original image had good result binary work after high pass- filter execution. In the case of using partial discharge of the image, our research could predict the last destruction timestamp. By means of experimental data, this Prediction system was acquired ${\pm}$3.2% error range.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.780-791
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• 1996

A hybrid image processing system which automatically distinguished lean tissues in the image of a complex beef cut surface and generated the lean tissue contour has been developed. Because of the in homegeneous distribution and fuzzy pattern of fat and lean tissue on the beef cut, conventional image segmentation and contour generation algorithm suffer from a heavy computing requirement, algorithm complexity and poor robustness. The proposed system utilizes an artificial neural network enhance the robustness of processing. The system is composed of pre-network , network and post-network processing stages. At the pre-network stage, gray level images of beef cuts were segmented and resized to be adequate to the network input. Features such as fat and bone were enhanced and the enhanced input image was converted tot he grid pattern image, whose grid was formed as 4 X4 pixel size. at the network stage, the normalized gray value of each grid image was taken as the network input. Th pre-trained network generated the grid image output of the isolated lean tissue. A training scheme of the network and the separating performance were presented and analyzed. The developed hybrid system showed the feasibility of the human like robust object segmentation and contour generation for the complex , fuzzy and irregular image.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.118.5-118
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• 2001

This paper describes an image processing method for inspecting the surface outlook of high speed moving plates. Noise free image and a new real time processing methods are required to inspect the surface outlook of the high speed moving plates in real time. It is difficult to get a noise free image due to a signal noise, a light noise and background image in typical industrial factory. Thus, pre-processing techniques should be required to get a good image and produce so many time steps to proceed the image data. The objective of this research is to get image on the surface of the moving plates with a speed of 1m/sec and to detect some defaults on the surface image. So, the pre-processing techniques ...

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.14 no.1
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• pp.26-33
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• 2001

The proposed system was composed of pre-processor which was executing binary/high-pass filtering and post-processor which ranged from statistic data to prediction. In post-processor work, step one was filter process of image, step two was image recognition, and step three was destruction degree/time prediction. After these processing, we could predict image of the last destruction timestamp. This research was produced variation value according to growth of tree pattern. This result showed improved correction, when this research was applied image Processing. Pre-processing step of original image had good result binary work after high pas- filter execution. In the case of using partial discharge of the image, our research could predict the last destruction timestamp. By means of experimental data, this prediction system was acquired $\pm$3.2% error range.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.5
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• pp.24-32
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• 2010

In this study, we have proposed a pre-processing algorithm newly developed for improving the tracking efficiency of the optical flow method. The developed pre-processing algorithm consists of a median filter, binarization, morphology, canny edge, contour detecting and an approximation method. In order to evaluate whether the optical flow tracking capacity increases, this study applied the pre-processing algorithm to the Lucas-Kanade(LK) optical flow algorithm, and comparatively analyzed its images and tracking results with those of optical flow without the pre-processing algorithm and with the existing pre-processing algorithm(composed of median filter and histogram equalization). As a result, it was observed that the tracking performance derived from the LK optical flow algorithm with the pre-processing algorithm, shows better tracking accuracy, compared to the one without the pre-processing algorithm and the one with the existing pre-processing algorithm. It seems to have resulted by successful segmentation for characteristic areas and subdivision into inner and outer contour lines.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1164-1170
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• 2011

In this paper, we propose accurate lattice extraction of elemental image array and pre-processing methods in computational integral imaging. Pre-processing methods remove distortions and noises of the image. Such distortions occurred in pickup systems are rotational errors. Distortions will degrade the resolution of reconstructed images. To overcome this problem, we propose our methods for extraction of elemental image array and pre-processing methods. Also, we describe that distortions affect the high quality reconstruction. Optical and computational experiments indicate that reconstructed images applied our methods is better than reconstructed images unapplied our methods.

• Journal of Electrical Engineering and information Science
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• v.1 no.1
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• pp.70-76
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• 1996

In this paper, we have proposed a band stop filter (BSF) for pre-processing of image sequences before encoding. By pixel-wise temporal filtering of the image sequences using the BSF, the bandwidth and noise of the signal are reduced, while preserving the image quality in view of human visual perceptions. As a result, when compared to the original image sequences, te pre-filtered image sequence requires lower bit-rates for encoding, while there is not much degradation in quality. Also, it has been shown that the proposed BSF causes less smearing and blurring than the conventional recursive low pass filter for bandwidth and noise reductions.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2565-2574
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• 2000

The error diffusion method is good for reproducing continuous image to binary image. However the reproduction of edge characteristic is weak in power spectrum analysis of display error. In this paper. we present an edge-enhanced error-diffusion method which include pre-processing algorithm for edge characteristic enhancement. Pre-processing algorithm consists of the difference value between current pixel and local average of original image and weighting function of pre-filter. First. it is obtained the difference value between current pixel and the local average of peripheral pixels(5x5) in original image. Second, weighting function of pre-filter is composed by function including absolute value and sign of difference value. The improved Error diffusion algorithm using pre-processing algorithm, present a good result visually which edge characteristic is enhanced. The performance of the proposed algorithm is compared with that of the conventional edge-enhanced error diffusion by measuring the RAPSD of display error, the egde correlation and the local average accordance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.999-1002
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• 2013

There are numerous image processing systems these are usually depend on high performance processors. However, systems using high performance processors might not be proper to mobile applications or low-power systems. Therefore, more efficient methodology for image processing is required for variable applications. This paper proposed pre-processing method using intra prediction concept in order to reduce processing range in a image picture(frame) and entire processing time. Also, the system configuration based on intra prediction hardware core and implementation result of the hardware core are presented in this paper.