• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.851-854
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• 2000

Digital halftoning is a technique to make an equivalent binary image from scanned photo or graphic images. Low pass filtering characteristic of human visual system can be applied to get the effect of spatial averaging of local area consisted of black and white pixels for gray image. The overlapping of black dot decreases brightness and black dot is very sensitive to human visual system in the bright region. In this paper, for gray-level expression, only bright gray region in the color image is considered for blue noise mask (BNM) approach. To solve this problem, BNM with CMY dot is used for the bright region instead of black dot. Dot-on-dot model with single mask causes the problem making much black dot overlap, color distortion. Therefore approach with three masks for C, M and Y each is proposed to decrease pixel overlap and color distortion.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.29 no.2
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• pp.417-422
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• 1999

Purpose : The aim of this study was to assess the validity of standard deviation of gray scale histogram in digital subtraction radiography as a test parameter for superimposition error. Materials and Methods : Twenty periapical radiographs were used as baseline images and they were copied to exclude the influence of exposure geomety and contrast differences. These subsequent images were linearly displaced by 0.1-0.5 mm in the x-. y- and xy-directions, rotated by 0.5-3° and distorted by angular contraction of 1-5° in x- and y-axis before subtraction. The standard deviations of gray levels in the subtraction images were obtained and paired t-tests were performed. Pearson correlation coefficients(r) were calculated between the standard deviations and the superimposition errors. Results : Linear displacement showed high correlation coefficients of 0.997, 0.997 and 0.995 in x-. y- and xy-axis respectively. Statistically significant different standard deviation existed among all linearly displaced groups(p<0.05). Distortion showed relatively low correlation coefficients of 0.982 and 0.959 in x- and y-axis. The standard deviations between the two distortion groups were statistically significant different(p<0.05). Conclusion : Standard deviation of gray level distribution in digital subtraction images is satisfactory but not perfect similarity measure to assess the superimposition errors.

• Journal of Korea Multimedia Society
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• v.3 no.2
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• pp.112-120
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• 2000

In this paper, we implement a real-time textile dimension inspection system. It can detect various types of real defects which determine the quality of fabric product, defect positions of textile, classify the distortion angel of moving textile and the density. In the implemented system, we measure the density of textile using zone-crossing method with optical lens to solve the noise and real-time problems. And we compensate distortion angel of textile with the classification of distortion types using gaussian gradient and mean gradient features. And also, it detecs real defects of textile and its positions using gray level co-occurrence matrix features. The implemented texile demension inspection systemcan inspect textile dimensions such as density, distortion angle, defect of textile and defect position at real-time. In the implemented proposed texitile dimension inspection system, It is possible to calculate density and detect default of textile at real-time dimension inspection system, it is possible to calculate density and detect default of textile at textile states throughout at all the significant working process such as dyeing, manufacturing, and other texitle processing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.901-906
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• 2004

For a digital image watermarking some autostereograms are used such as random dot images. In there, the extraction efficiency is good and the distortion rate is low. In this paper, we shall select an optimized scaling parameter which derives low distortion rate and high extraction efficiency, when we use a random dot images as like as autostereograms into some images except for extremely biased gray level images.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.3
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• pp.126-131
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• 1998

In computer vision system of modern industry precise measuring has lots of dfficulties because of measurement error due to distortion phenomenon. Among the difficulties, the distortion of edge is regraded as a dominent problem. which is caused by the vlurred image. The blurred image apperar when camera can not discriminate its precise focus. So. it is very important to decide focus of lens and to develop algorithm in order to correct distortion phenomenon. Thus. discrimination criteria obtained by image information of precise focus must be fixed in advance. The gray level histogram of image acquired from blurred edge tends to show a uniform distribution. Bimodal intensity histogram is related with condition of focus, and it is possible to find good condition of focus by using bimodal histogram of entropy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.716-725
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• 2005

In this paper, we propose a new approach for the reduction of the dynamic false contours, which detects and compensates false contour artifacts adaptively. First, we develop a simple but effective method to select the pixels that are likely to cause the motion artifacts, based on the distribution of pixel values. Then, we merge the selected pixels into several regions using tree structure. Next, we reduce number of gray levels within the regions slightly to reduce the false contours. Note that reducing number of gray levels yield the distortion, thus it is applied only to the selected regions, instead of the whole picture. Intensive simulations on real moving image show that the proposed algorithm alleviates the dynamic false contours effectively with tolerable computational complexity.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.10
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• pp.118-125
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• 1998

We introduce an adaptive finite state vector quantization using a new side match distortion function. The conventional side match distortion function can make the gray level transition between the block bounddaries as smooth as possible and proper state codebooks in the flat areas where the spatial correlations are high. But it can't make proper codebooks in the edge areas where the spatial correlations are not high. The proposed distortion function adds the variances which represent the image characteristics to the conventional side match distortion function as weighted values. Then it can select better state codebooks than the conventional side match distortion function. Also if it predicts a wrong state, the proposed quantizer can correct the state. As a result, we can obtain the satisfiable image quality.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.487-490
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• 2001

With the establishment of the optimized copyright, digital image watermarking technique is demended to identify the owner of a certain image and to avoid the unauthorized distribution of digital image copies. Also, a robust watermarking approach should survive several possible attacks, such as image processing and lossy image compession. The proposed scheme distributes the 256 gray-level signature information in discrete wavelet transform domain of the host image where is very little visible distortion. While much of the privious work used signature data that is a small fraction of th e host images the proposed approach can easily handle gray-scale Images. As the result, stable reconstruction can be obtained even when the images are transformed, JPEG lossy compression or otherwise modified by low-pass filtering operations.

• Journal of IKEEE
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• v.13 no.2
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• pp.224-231
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• 2009

Unsharp masking is a popular image enhancement technique used to sharpen an image appearance in gray images. However, the conventional unsharp making techniques amplify the noise and easily cause overshoot artifacts. Moreover, the unsharp masking tends to introduce color distortion when it is applied to the each color component independently. To solve these problems, we propose a novel unsharp masking technique based on human visual system and vector projection. The proposed algorithm consists of two steps. First, the proposed algorithm controls the level of sharpening by exploiting the characteristics of the human visual system and contrast region. Then the vector projection is applied to remove the color distortion. Experiment results show that our proposed algorithm successfully produces sharpened images that are free of noise and color distortion commonly found in the conventional unsharp masking algorithms.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.89-92
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• 2002

In this paper we present a barcode reader to decode two-dimensional symbology PDF-417 and propose a novel method to extract the bar-space patterns directly from the gray-level barcode image, which employs the location and the distance between extreme points of each row of the barcode image. This algorithm proves to be very robust from the high convolution distortion environments such as defocussing and warping, even under badly illuminating condition. If the scanned barcode image is a result of the convolution of a Gaussian-shaped point spread function with a bi-level image, popular image segmentation methods such as image thresholding can not distinguish between very narrow bar-space patterns with a couple of pixels wide. The proposed algorithm shows improved performance over current barcode readers.