• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.728-734
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• 1998

Aircraft noise is one of the main causes of environmental impact. It is more serious than any other noise nuisance. It has become an increasing source of annoyance to the large number of people who live in communities near airports. This paper demonstrates the prediction of aircraft noise using Integrated Noise Model(INM) 5.1 developed by U.S. FAA and aircraft noise contour map near airports.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.110-116
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• 2000

Aircraft noise is one of the main causes of environmental impact. It is more serious than any other noise nuisance. It has become an increasing source of annoyance to the large number of people who live in communities near airports. This paper demonstrates the prediction of aircraft noise using Integrated Noise Model (INM) 5.1 developed by U.S. FAA and aircraft noise contour map near airports.

• Journal of Broadcast Engineering
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• v.15 no.5
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• pp.697-702
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• 2010

Contour artifact is known as the unintentional result of quantizing a flat area that has smooth gradients. In this letter, a decontouring algorithm is proposed to efficiently remove false contours that occur in typical block-based video coding applications. First, the algorithm goes through a refinement stage to determine candidate blocks probably having noticeable false contours with different kinds of features in a block. Then, pseudo-random noise masking is applied to those blocks to mitigate the contour artifacts. This block-based selective decontouring can efficiently remove the unnecessary processing of those blocks that have no false contour, which incidentally ensures a minor penalty in visual quality and computational complexity. The proposed algorithm was demonstrated, integrated into H.264/AVC, that visual quality can be significantly enhanced with an ignorable rate-distortion (RD) loss and an minor increase in computational complexity.

• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.3
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• pp.296-301
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• 2012

This paper describes an analytic method for infrared thermography to detect surface cracks in thin plates. Traditional thermographic method uses the spatial contrast of a thermal field, which is often corrupted by noise in the experiment induced mainly by emissivity variations of target surfaces. This study developed a robust analytic approach to crack detection for thermography using the holomorphic function of a temperature field in thin plate under steady-state thermal conditions. The holomorphic function of a simple temperature field was derived for 2-D heat flow in the plate from Cauchy-Riemann conditions, and applied to define a contour integral that varies depending on the existence and strength of singularity in the domain of integration. It was found that the contour integral at each point of thermal image reduced the noise and temperature variation due to heat conduction, so that it provided a clearer image of the singularity such as cracks.

• Journal of the Korea Society of Computer and Information
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• v.4 no.4
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• pp.77-85
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• 1999

In this paper. improved the formula of Kass. First of all, improved initial guess inside and outside of an object. So, prevent the of shrink, find more easily and faster the contour of object. Secondly, proposed the algorithm which moved to local minimum with the improvement of formula of the internal energy and $3{times}3$ matrix. Process the noise of local minimum with use of medial filtering. In third, process the phenomenon which edge points gather one point with imposing energy to the energy term. Improve the algorithm to find the contour precisely with the use of threshold. The result of these improvements, make an initial guess easily and find the contour of objects which have higher curvature. Improve the speed of process by reducing the repetition of feedback system.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.231-234
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• 2002

This paper proposes a new approach to extract contour of moving object from compressed video stream. We segment the area of moving object by using motion vector and extract the motion object block from it. And then we describe the connectivity direction of outline moving block, detect the edge related to connectivity direction in the block and finally obtain the contour by connecting the edges. This can divide the moving object only with motion vector and detect the exact contour on the basis of the edge automatically. Also, we can reduce spending time using motion block and remove the noise with directional edge. The experimental results demonstrate the accurate and effective qualify of the proposed method.

• Journal of Digital Convergence
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• v.10 no.3
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• pp.167-172
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• 2012

This paper presents the technique separating objects on the single frame image from the background using region segmentation technique based on active contour. Active contour is to extract contours of objects from the image, which is set to have multi-search starting point to extract each objects contours for multi-object segmentation. Initial rough object segments are generated from binary-coded image using object specific contour information, and then the hole filling is performed to compensate internal segmentation caused by the change of inner object hole area and pixels. This procedure complements the problems caused by the noise from the region segmentation and the errors of segmentation near by the contour. The proposed method and conventional method is compared to verify the superiority of the proposed method.

• Fisheries and Aquatic Sciences
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• v.4 no.1
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• pp.10-17
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• 2001

One serious problem among the troubles to identify objects in an optical microscopic image is contour background due to non-uniform light source and various transparency of samples. To solve this problem, this paper proposed an elimination method of the contour background and compensation technique as follows. First, Otsu's optimal thresholding method extracts pixels representing background. Second, bilinear interpolation finds non-deterministic background pixels among the sampled pixels. Third, the 2D cubic fitting method composes surface function from pivoted background pixels. Fourth, reconstruction procedure makes a contour image from the surface function. Finally, elimination procedure subtracts the approximated background from the original image. To prove the effectiveness of the proposed algorithm, this algorithm is applied to the yeast Zygosaccharomyces rouxii and ammonia-oxidizing bacteria Acinetobacter sp. Labeling by this proposed method can remove some noise and is more exact than labeling by only Otsu's method. Futhermore, we show that it is more effective for the reduction of noise.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.5
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• pp.1996-2001
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• 2012

Visual inspection systems are widely proposed for the well formed surface materials like electronics parts. But the materials with ill reflection ability have many troubles when visual inspection system is introduced. We have developed a robust visual inspection system that can work well in spite of low reflection ratio and with much noise when truth model is not known in the mixed production line. A workpiece identification technique using k-means has been proposed to identify the type. Based on the identified type, a robust-to-noise segmentation method, called active contour, has been applied to segment the features from the image. Finally, Kalman filter has been applied to adapt the error variation. Experiment shows that performance is about to match the accuracy of manual measurement using projectors.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.10
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• pp.69-77
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• 1992

Pattern Recognition is one of the fundamental areas of computer vision. The recognition of patterns with varying size and severe defects is especially important. However, it is known that the conventional algorithms such as GHT or structural approaches have limitations in speed and accuracy. In this paper, in order to avoid above-mentioned problems, we propose a new recognition algorithm which exploits the histogram of contour directions and the sampled spot matching method. While the former provides little influence against size variation, the latter has strong immunity to noise and defects. We applied those proposed algorithms for the recognition of numbers extracted from the car number plates and shapes of aircraft. Experimental result shows that it is possible to solve above-mentioned problems by complementary uses of those two suggested algorithms. The contour directional histogram method resulted in high-speed of average 0.013 sec/char and 0.1 sec/aircraft-image on IBM-386. The accuracy of recognition is as high as 99%. Sampled spot matching method has less speed than the former one, however, it showed fairly strong immunity to noise and defects.