• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.707-715
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• 2008

This paper proposes an algorithm for efficient compression gray-level images by entropy encoder. The issue of the proposed method is to replace original data of gray-level images with particular ranked data. For this, first, before encoding a stream of gray-level values in an image, the proposed method counts co-occurrence frequencies for neighboring pixel values. Then, it replaces each pay value with particularly ranked numbers based on the investigated co-occurrence frequencies. Finally, the ranked numbers are transmitted to an entropy encoder. The proposed method improves the performance of existing entropy coding by transforming original gray-level values into rank based images using statistical co-occurrence frequencies of gray-level images. The simulation results, using gray-level images with 8-bits, show that the proposed method can reduce bit rate by up to 37.85% compared to existing conventional entropy coders.

• Imaging Science in Dentistry
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• v.32 no.3
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• pp.147-151
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• 2002

Purpose: To compare the standard deviation of gray levels on digital subtracted images obtained by different dental subtraction programs. Materials and Methods: Paired periapical films were taken at the lower premolar and molar areas of the phantoms involving human mandible. The bite registration group used Rinn XCP equipment and bite registration material, based on polyvinyl siloxane, for standardization. The no bite registration group used only Rinn XCP equipment. The periapical film images were digitized at 1200 dpi resolution and 256 gray levels by a flat bed scanner with transparency unit. Dental digital subtraction programs used for this study were Subtractor (Biomedisys Co., Korea) and Emago (Oral Diagnostic Systems, The Netherlands). To measure the similarities between the subtracted images, the standard deviations of the gray levels were obtained using a histogram of subtracted images, which were then analyzed statistically. Results: Subtracted images obtained by using the Emago program without manual selection of corresponding points showed the lowest standard deviation of gray levels (p<0.01). And the standard deviation of gray levels was lower in subtracted images in the group of a bite registration than in the group of no use of bite registration (p < 0.01). Conclusion: Digital radiographic subtraction without manual selection of reference points was found to be a convenient and superior method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.1-10
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• 2008

Coloriztion algorithms, which hide color information into gray images and find them to recover color images, have been developed recently. In these methods, it is important to minimize the loss of original information while the color components are embedded and extracted. In this paper, we propose a colorization method using a wavelet packet transform in order to embed color components with minimum loss of original information. In addition, the compensation processing of color saturation in the recovered color images is achieved. In the color-to-gray process, an input RGB image is converted into Y, Cb, and Cr images, and a wavelet packet transform is applied to the Y image. After analyzing the amounts of total energy for each sub-band, color components are embedded into two sub-bands including minimum amount of energy on the Y image. This makes it possible not only to hide color components in the Y image, but to recover the Y image with minimum loss of original information. In the gray-to-color process, the color saturation of the recovered color images is decreased by printing and scanning process. To increase color saturation, the characteristic curve between printer and scanner, which can estimate the change of pixel values before and after printing and scanning process, is used to compensate the pixel values of printed and scanned gray images. In addition, the scaling method of the Cb and Cr components is applied to the gray-to-color process. Through the experiments, it is shown that the proposed method improves both boundary details and color saturation in the recovered color images.

• Journal of the Korean Academy of Clinical Electrophysiology
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• v.8 no.2
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• pp.39-43
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• 2010

Purpose : The purpose of this study was to analyze skin reactions induced by ultraviolet irradiation using digital imagery. Methods : We recruited 15 women and ultraviolet irradiation was applied to their lumbar area. (The degree of inflammatory reaction was set on the basis of the third erythema dose. Image analysis was divided by Photoshop CS (8 bit RGB scale and gray scale). Then, images were processes using Image Pro Plus 4.5 program analyzing R, G, B, chromatic red value, luminance value and gray value. Results : As a result of analyzing changes in RGB scale, there were statistically significant differences in R, G, and chromatic red values. As a result of analyzing changes in gray scale, there were statistically significant differences in gray value. Analysis of changes in B and luminance values showed that there was no statistically significant difference. Conclusion : This study found that ultraviolet irradiation had influence on RGB and gray scale. These results suggest that changes to digital images on skin reaction by ultraviolet irradiation are related to erythema. In particular, these changes are related to R and gray values.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.1035-1041
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• 2016

Internal cracks in products are invisible and can lead to fatal crashes or damage. Since X-rays can penetrate materials and be attenuated according to the material’s thickness and density, they have rapidly become the accepted technology for non-destructive inspection of internal cracks. This paper presents a robust crack filter based on local gray level variation and multiscale analysis for automatic detection of cracks in X-ray images. The proposed filter takes advantage of the image gray level and its local variations to detect cracks in the X-ray image. To overcome the problems of image noise and the non-uniform intensity of the X-ray image, a new method of estimating the local gray level variation is proposed in this paper. In order to detect various sizes of crack, this paper proposes using different neighboring distances to construct an image pyramid for multiscale analysis. By use of local gray level variation and multiscale analysis, the proposed crack filter is able to detect cracks of various sizes in X-ray images while contending with the problems of noise and non-uniform intensity. Experimental results show that the proposed crack filter outperforms the Gaussian model based crack filter and the LBP model based method in terms of detection accuracy, false detection ratio and processing speed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.91-102
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• 1994

For the analysis of textured image, it requires large storage space and computation time to calculate the matrix features such as SGLDM(Spatial Gray Level Dependence Matrix). NGLDM(Neighboring Gray Level Dependence Matrix). NSGLDM(Neighboring Spatial Gray Level Dependence Matrix) and GLRLM(Gray Level Run Length Matrix). In spite of a large amount of information that each matrix contains, a set of several correlated scalar features calculated from the matrix is not sufficient to approximate it. In this paper, we propose a new classifier for textured images based on these matrices in which the projected vectors of each matrix on the meaningful directions are used as features. In the proposed method, an unknown image is classified to the class of a known image that gives the maximum similarity between the projected model vector from the known image and the vector from the unknown image. In the experiment to classify images of agricultural products, the proposed method shows good performance as much as 85-95% of correct classification ratio.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.283-286
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• 2001

Based on a fuzzy system representation of gray scale images, we derive an edge detection algorithm whose convolution kernel is different from the known kernels such as those of Roberts', Prewitt's or Sobel's gradient. Our fuzzy system representation is an exact representation of the bicubic spline function which represents the gray scale image approximately. Hence the fuzzy system is a continuous function and it provides a natural way to define the gradient and the Laplacian operator. We show that the gradient at grid points can be evaluated by taking the convolution of the image with a 3 3 kernel. We also show that our gradient coupled with the approximate value of the continuous function generates an edge detection method which creates edge images clearer than those by other methods. A few examples of applying our methods are included.

• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.502-511
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• 2005

In this paper, we propose a hybrid analysis method(HAM) based on gray-intensity information from natural scene images. The HAM is composed of GIA(Gray-intensity Information Analysis) and SMA(Split/Merge Analysis). Our experimental results show that the proposed approach is superior to conventional methods both in simple and complex images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.8
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• pp.459-466
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• 2014

Fading effect of old pictures and printings is shown up differently according to the ink property, temperature, humidity, illuminants, and so on. Faded image enhancement techniques based on illuminant estimation are proposed such as the gray world algorithm and white patch retinex methods. However, conventional simple operators are not suitable for enhancing faded images because partial fading effect is appeared differently. Thus, this paper presents a color enhancement algorithm based on integrating correction coefficients for faded images. First, the proposed method adopts local process by using multi-scale average mask. The coefficients for each multi-scale average mask are obtained to apply the gray world algorithm. Then, integrating the coefficients with weights is performed to calculate correction ratio for red and blue channels in the gray world assumption. Finally, the enhanced image is obtained by applying the integrated coefficients to the gray world algorithm. In the experimental results, the proposed method reproduces better colors for both wholly and partially faded images compared with the previous methods.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.1
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• pp.68-78
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• 2005

A new emotion-based image retrieval method is proposed in this paper. The research was motivated by Soen's evaluation of human emotion on color patterns. Thirteen pairs of adjective words expressing emotion pairs such as like-dislike, beautiful-ugly, natural-unnatural, dynamic-static, warm-cold, gay-sober, cheerful-dismal, unstablestable, light-dark, strong-weak, gaudy-plain, hard-soft, heavy-light are modeled by 19-dimensional color array and $4{\times}3$ gray matrix in off-line. Once the query is presented in text format, emotion model-based query formulation produces the associated color array and gray matrix. Then, images related to the query are retrieved from the database based on the multiplication of color array and gray matrix, each of which is extracted from query and database image. Experiments over 450 images showed an average retrieval rate of 0.61 for the use of color array alone and an average retrieval rate of 0.47 for the use of gray matrix alone.