• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.87-91
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• 2011

In this paper, we propose a new deinterlacing method that converts the interlaced images into the progressive images using a field. Firsr of all, it estimates the direction of edge. If it makes an accurate estimate of the direction, then it interpolates a pixel using ELA(Edge-based Line Average). Otherwise, it estimates the new direction of edge, and then,, it interpolates a pixel using a proposed median filter. From simulation results, it is shown that the proposed method improves both subjective and objective image quality as compared with previous deinterlacing methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9C
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• pp.725-733
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• 2008

This paper proposed a novel do-interlacing algorithm using all direction edges estimation technique. In the proposed algorithm. previously developed the DOI(Direction-Oriented Interpolation) algorithm was used as a basis. The do-interlacing method was divided into two main parts. First, we should estimate edge direction. Then, missing pixel: were interpolated along with the decided edge. In this paper, after estimating the edge through the DOI algorithm considering high angle edge direction, missing pixels were interpolated by using the median filter. Experimental results indicate that the proposed algorithm is superior to the conventional algorithms in terms of the objective and subjective criteria.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.87-94
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• 2008

In this paper, we present a directional error concealment technique to compensate a lost block. Generally, the strong edge of an image has the large amounts of the variance because of its large coefficients in the wavelet domain. For estimating edge direction of a lost block, a $X^2$ hypothesis-testing problem is applied using the variance of wavelet coefficients. The lost block is interpolated according to the estimated edge direction. The pixels for interpolation is obtained from the edge direction. The proposed method outperforms the previous methods in objective and subjective qualities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.900-902
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• 2015

In the modern society, according to the advancement in digital image processing technology, edge detection is being utilized in various application sectors such as smart device and medical, etc. In existing edge detection methods, there are Sobel, Prewitt, Roberts and Laplacian, etc, which uses the mask. These previous methods are easy to implement but shows somewhat insufficient results. Therefore, in order to compensate the problems of existing methods, in this paper, an algorithm that detects the edge using the local mask and morphological operation was proposed and the detection performance was compared against the previous methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.3
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• pp.249-262
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• 1989

We present a method of boundary extraction of moving objects. We propose four methods for detecting moving edge pixels which can be located on the boundaries of moving objects. We select the best one after we test the above four methods to real image sequences. The portion of the boundaries of moving objects which is marked as moving edge pixels is searched along the moving edge pixels with simple heuristics. And the end points of the resultant line segments are utilized as the start points of the secon stage heuristic search. This second stage search is performed for the boundaries of moving objects which is not marked as moving edge pixels due to various reasons. We test our algorithm for two real sequences and we find that this simple algorithm has good performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.6000-6017
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• 2018

This paper presents a new descriptor, named Histograms of Prominent Edge Directions (HPED), for the recognition of facial expressions in a person-independent environment. In this paper, we raise the issue of sampling error in generating the code-histogram from spatial regions of the face image, as observed in the existing descriptors. HPED describes facial appearance changes based on the statistical distribution of the top two prominent edge directions (i.e., primary and secondary direction) captured over small spatial regions of the face. Compared to existing descriptors, HPED uses a smaller number of code-bins to describe the spatial regions, which helps avoid sampling error despite having fewer samples while preserving the valuable spatial information. In contrast to the existing Histogram of Oriented Gradients (HOG) that uses the histogram of the primary edge direction (i.e., gradient orientation) only, we additionally consider the histogram of the secondary edge direction, which provides more meaningful shape information related to the local texture. Experiments on popular facial expression datasets demonstrate the superior performance of the proposed HPED against existing descriptors in a person-independent environment.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.9
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• pp.789-796
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• 2013

Vibration measurements using image processing have been studied by many researchers as it can remotely measure vibration displacements at multiple points simultaneously. It is difficult, however, to obtain accurate displacement from the measured image signals because the resolution of image data is dependent on camera performance and normally lower than that of vibration transducer directly measured. This paper suggests the enhanced technique for vibration displacement measurement by applying the expected value of edge probability distribution to the varying pixel points in the image. The method can both increase the resolution limit of camera image and decrease the measurement errors. The working performance of the proposed technique is verified applying to the vibration measurement of a rotating machine.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.73-76
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• 2001

We propose a new method for image coding that it is based on highly related property between a spatial image and wavelet transform image. The characteristics have an important role in the design of proposed algorithm. This algorithm for image coding is to obtain high compression rate at low bit rate. The other side, the high activity regions are related to significant coefficients which give much influence to image reconstruction, because they mean the important factor to represent the appearance of images such as edge or boundary. For some images with low activity, we can obtain the reconstructed image with near to 30 dB at 150: 1 compression ratio.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.591-596
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• 2011

Image denoising is a key issue in all image processing researches. Generally, the quality of an image could be corrupted by a lot of noise due to the undesired conditions of image acquisition phase or during the transmission. Many approaches to image restoration are aimed at removing either Gaussian or impulse noise. Nevertheless, it is possible to find them operating on the same image, which is called mixed noise and it produces a hard damage. In this paper, we proposed noise type classification method and a mixed nonlinear filter for mixed noise suppression. The proposed filtering scheme applies a modified adaptive switching median filter to impulse noise suppression and an efficient nonlinear filer was carried out to remove Gaussian noise. The simulation results based on Matlab show that the proposed method can remove mixed Gaussian and impulse noise efficiently and it can preserve the integrity of edge and keep the detailed information.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1207-1214
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• 2009

In this study, we propose a novel color-image segmentation algorithm to discern the teeth region utilizing RG intensity and its relevant RGB histogram features with resolving the variations of its maximum intensity in terms of peaks and valleys. Tooth candidates in a CCD image are first extracted by applying RGB color multi-threshold levels and consequently the successive morphological image operations and a Sobel-mask edge processing are performed to resolve the teeth region and its contour.