• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.99-102
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• 2009

In this paper a hierarchical stereo matching algorithm based on feature extraction is proposed. The boundary (edge) as feature point in an image is first obtained by segmenting an image into red, green, blue and white regions. With the obtained boundary information, disparities are extracted by matching window on the image boundary, and the initial disparity map is generated when assigned the same disparity to neighbor pixels. The final disparity map is created with the initial disparity. The regions with the same initial disparity are classified into the regions with the same color and we search the disparity again in each region with the same color by changing block size and search range. The experiment results are evaluated on the Middlebury data set and it show that the proposed algorithm performed better than a phase based algorithm in the sense that only about 14% of the disparities for the entire image are inaccurate in the final disparity map. Furthermore, it was verified that the boundary of each region with the same disparity was clearly distinguished.

• Journal of Digital Contents Society
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• v.8 no.3
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• pp.365-370
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• 2007

This paper proposes a new algorithm that generates a panorama image for reconstruction of image-based virtual environment. Proposed algorithm can generate panorama image from input images using the projective transform based on the feature model and a fully immersive image-based virtual environment according to the user's view point by the sphere mapping. Especially, proposed algorithm supports robust methods of camera rotation and is applied to various images to estimate ist performance.

• Current Optics and Photonics
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• v.2 no.4
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• pp.315-323
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• 2018

A new multiple-image encryption scheme that is based on a compressive ghost imaging concept along with a Fourier transform sampling principle has been proposed. This further improves the security of the scheme. The scheme adopts a Fourier transform to sample the original multiple-image information respectively, utilizing the centrosymmetric conjugation property of the spatial spectrum of the images to obtain each Fourier coefficient in the most abundant spatial frequency band. Based on this sampling principle, the multiple images to be encrypted are grouped into a combined image, and then the compressive ghost imaging algorithm is used to improve the security, which reduces the amount of information transmission and improves the information transmission rate. Due to the presence of the compressive sensing algorithm, the scheme improves the accuracy of image reconstruction.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.12
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• pp.653-659
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• 2001

In this paper, we propose an efficient algorithm for constructing cylindrical panoramic image. At first, we describe a fast image alignment algorithm, which matches image strips located on equal distance for image centers. And then, we explain how to estimate accurately the effective focal length of camera by a bisection method. Although there is a limitation in that the image should be taken by a camera with pure panning motion, the proposed simple and fast algorithm is applicable to practical application.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.3
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• pp.140-147
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• 2013

We present a vaguelette-curvelet decomposition based image deblurring algorithm. We first perform denoising based on the hard-thresholding rule by estimating unknown curvelet coefficients. The proposed algorithm then calculates vaguelette functions by deconvolving the curvelet bases by the point spread function. Vaguelette transform is finally performed to make a clearly restored image. Since the proposed algorithm uses the curvelet transform to sensitively express the edges in all directions, it is possible to restore images with more naturally preserved edges in all directions.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.193-195
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• 2006

As multimedia information increases sharply, In image retrieval field the method that can analyze image data quickly and exactly is required. In the case of image data, because each data includes a lot of informations, between accuracy and speed of retrieval become trade-off. To solve these problem, feature vector extracting process that use Genetic Algorithm for implementing prompt and correct image clustering system in case of retrieval of mass image data is proposed. After extracting color and texture features, the representative feature vector among these features is extracted by using Genetic Algorithm.

• Journal of Biosystems Engineering
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• v.30 no.5 s.112
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• pp.299-305
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• 2005

This study was developed image processing algorithm for recognition of few teats of a cow in the image using black and white camera attached with infrared filter. Spectroscopic analysis was used for selection of a NIR filter to separate teats from udder skin in the image captured. To verify the performance of image processing algorithm was developed and NIR filter was selected, carried out an experiment with cows. NIR band-pass filter was used to pass the 975nm band of light spectrum. The image processing algorithm was developed could recognize all teats and the process time was 0.9 second to recognize the all teats and to acquire end position of teats.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.6
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• pp.594-599
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• 2008

Image data produced from ADD water-tunnel test are currently analyzed manually. The accuracy and elapsed time of this process can be determined by observers. In this paper, the algorithm based on MATLAB for improved image data processing and analysis is proposed. This algorithm consists of camera calibration, gray-level transformation, noise filtering and binarization in image preprocessing, vortex trajectory measurement in image analysis. Experimental results show that the proposed algorithm has better accuracy and execution speed than those of the existing methods.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.4
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• pp.197-205
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• 2019

In this paper, an efficient single dehazing algorithm is proposed based on linear transformation by assuming that a linear relationship exists in saturation component between the haze image and haze-free image. First, we analyze the linearity of saturation channel, estimate the medium transmission map in terms of the saturation component. Then, the intensity of haze-free image is assumed by using CLAHE to enhance contrast of haze image. Experimental results demonstrate that proposed algorithm can naturally recover the image, especially can remove color distortion caused by conventional methods. Therefore, our approach is competitive with other state-of-the art single dehazing methods.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.3
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• pp.133-142
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• 2019

The existing auxiliary communicating aids for the hearing-impaired have an inconvenience of using additional expensive sensing devices. This paper presents a hand image detection based algorithm to interpret the sign language of the hearing-impaired. The proposed sign language recognition system exploits the hand image only captured by the camera without using any additional gloves with extra sensors. Based on the hand image processing, the system can perfectly classify several numeric sign language representations. This work proposes a simple lightweight classification algorithm to identify the hand image of the hearing-impaired to communicate with others even further in an environment of complex background. Experimental results show that the proposed system can interpret the numeric sign language quite well with an accuracy of 95.6% on average.