• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.28 no.2
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• pp.415-433
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• 1998

Digora system is an intraoral indirect digital radiography system utilizing storage phosphor image plate. It has wide dynamic range which allows it to decrease the patient s exposure time and may increase diagnostic ability through image processing (such as edge enhancement, grey scale conversion, brightness change, and contrast enhancement). And also, it can transmit and storage image information. The purpose of this study was to evaluate the diagnostic ability of artificial proximal caries between Conventional radiograph and Digora images(unenhanced image, brightness & contrast controlled image, and edge enhanced image). ROC(Receiver Operating Characteristic) analysis, paired t-tests, and F-tests were done for the statistical evaluation of detectability. The following results were acquired: 1. In Grade I lesions, the mean ROC areas of Conventional radiograph, Digora unenhanced image, Digora controlled image, and Digora edge enhanced image were 0.953, 0.933, 0.965, 0.978 (p>0.05). 2. In Grade II lesions, the mean ROC areas of Conventional radiograph, Digora unenhanced image, Digora controlled image, and Digora edge enhanced image were 0.969, 0.964, 0.988, 0.994. Among theses areas, there was just statistical significance between Diagnostic abilities of Digora edge enhanced image and Conventional radiograph (p<0.05). 3. In the Interobserver variability, the ROC curve areas of Digora edge enhanced image was lowermost in these areas, regardless of the Carious lesion depths. In conclusion, intraoral indirect digital system, Digora system, has the potential possibility as an alternative of Conventional radiograph in the diagnosis of proximal caries.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.294-298
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• 2009

In this study, we proposes the method to improve the quality of the image through the edge extraction more delicately. Our method is named ESII(Edge Sensitive Image Interpolation) and doesn't use the fixed parameter of the interpolation kernel. However, it changes the parameter of pixel which is interpolated to the high definition image using the proper information from the surrounding pixels. It reconstructs the image by using the LSE(Least Square Error) and determining the pixel values to make the CME(Camera Modelling Error) minimized. Compared to the conventional methods, suggested method shows the higher quality of subjective and objective image definition and lessons the computational complexity by separating the image into 1-D data.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.39-42
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• 2003

In this paper, we propose a background segmentation method in low resolution color image. A segmentation algorithm is based on color and edge information. In edge image, adaptive and local thresholds are applied to suppress paint boundaries. Through our experiments, the proposed algorithm efficiently segments background from objects.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.124-127
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• 1995

Due to the self-diffusion of nuclear spins, the edge of phantoms is enhanced in the magnetic resonance imaging (MRI), especially in the case of microscopy [1]. According to several published works, theory has been established that the edge enhancement is caused by the motion narrowing around bounded regions due to diffusions of nuclear spins during data acquisition. It is found, however, that the signal decreases due to the diffusion attenuation and image is distorted as edge of the image is sharpened. In this paper, we wilt investigate this signal loss during data acquisition and its effects on image, i.e., image edge enhancement due to the diffusion phenomenon. This result is new and different from the previously discussed edge enhancement due to the diffusion, namely, by motion narrowing effect or spin bouncing effect at the boundary.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.151-156
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• 2006

This paper presents an background edge generation based automatic algorithm for detection of moving objects under moving camera. Background image is generated by rotating the fixed the camera on the tripod horizontally, aligning and reorganizing this images. We develop an efficient approach for robust panoramic background edge generation as well as method of edge matching between input image and background image. We applied the proposed algorithm to real image sequences. The proposed method can be successfully realized in various monitoring systems like intrusion detection as well as video surveillance.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.111-115
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• 2020

In this paper, I proposed an effective technique for accurately predicting pixel values using edge components. Adjacent pixel values are similar to each other. That is, generally, similarity exists between adjacent pixels in an image. In the proposed algorithm, edge components are detected using the surrounding pixels in the first step, and pixel values are estimated using the edge components in the second step. Therefore, the prediction accuracy of the pixel value is improved and the prediction error is reduced. Pixel value prediction is a necessary technique for various applications such as image magnification and confidential data concealment. Experimental results show that the proposed method has higher prediction accuracy and fewer prediction error. Therefore, the proposed technique can be effectively used for applications such as image magnification and confidential data concealment.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.535-538
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• 2009

Speckle noise reduction for ultrasound CT image using morphological adaptive median filtering based on edge preservation is presented in this paper. Speckle noise is multiplicative feature and causes ultrasound image to degrade widely from transducer. An input image is classified into edge region and homogeneous region in preprocessing. The speckle is reduced by morphological operation on the 2D gray scale by using convolution and correlation, and edges are preserved. The adaptive median is processed to reduce an impulse noise to preserve edges. As the result, MAM of the proposed method enhances the image to about 10% in comparison with Winner filter by Edge Preservation Index and PSNR, and 10% to only adaptive median filtering.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.4
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• pp.405-413
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• 1987

In this paper, we have discussed three-type median filters(SQUARE, CROSS, X-SHAPE) that preserving edge in an original image while reducing random noise was introduced for image enhancement and edge detection on radar image. Since radar image have a number of parts of curve, we compared results produced by edge detection operater proposed for improving the parts of curve with results of using the existing edge detection methods, such as Roberts, Sobel, Prewitt, Laplacian and Kirsch.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4502-4512
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• 2014

This article presents a reformulation of the Grey Edge framework for colour constancy. Colour constancy is the ability of a visual system to perceive objects' colours independently of their scenes' illuminants. Colour constancy algorithms try to estimate the colour of an illuminant from image values. This estimation can later be used to correct the image as though it were taken under a white illuminant. The modification presented allows the framework to incorporate image-specific filters instead of the commonly used edge detectors. A colour constancy algorithm is proposed using PCA and FastICA linear component analyses methods for the construction of such filters. The results show that the proposed method improves the accuracies of the Grey Edge framework algorithms whilst on the other hand, achieving comparable accuracies with the state-of-the-art methods, but improving their time efficiencies.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.264-268
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• 2010

The purpose of this paper is to propose new techniques to match measured optical images by using the edge abstraction method and differentiation method based on image processing technology. To do this, we detect the matching template and non-matching template from each optical image. And then, we detect the edge parts of the overlaped image from comer edge abstraction method and remove noise image. At last, these data are related to applied first-order derivative operator. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.