• 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.

• 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.

• Journal of Korea Multimedia Society
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• v.20 no.1
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• pp.43-50
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• 2017

According to living environment, the number of deaths due to thyroid diseases increased. In this paper, we proposed an algorithm for recognizing a thyroid detection using texture analysis based on shape, gray level co-occurrence matrix and gray level run length matrix. First of all, we segmented the region of interest (ROI) using active contour model algorithm. Then, we applied a total of 18 features (5 first order descriptors, 10 Gray level co-occurrence matrix features(GLCM), 2 Gray level run length matrix features and shape feature) to each thyroid region of interest. The extracted features are used as statistical analysis. Our results show that first order statistics (Skewness, Entropy, Energy, Smoothness), GLCM (Correlation, Contrast, Energy, Entropy, Difference variance, Difference Entropy, Homogeneity, Maximum Probability, Sum average, Sum entropy), GLRLM features and shape feature helped to distinguish thyroid benign and malignant. This algorithm will be helpful to diagnose of thyroid nodule on ultrasound images.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1999.06a
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• pp.240-246
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• 1999

The effect of microstructure of gray cast iron disk was investigated by using a pad-on-disk type friction tester. Three different rotors with different microstructures were studied in this work. They showed a pearlitic matrix, a ferritic matrix, and a martensitic structure, respectively. All of them have graphite flakes in common. Drag tests at different pressure and speed conditions were carried out to study friction stability, temperature rise during drags. The rotor containing pearlitic matrix showed lower values of friction coefficient, small amount of temperature rise, and less fading. The results showed that gray cast iron disk containing pearlitic matrix has good friction characteristics.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.5 s.98
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• pp.48-57
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• 1999

Applications of thresholding technique are based on the assumption that object and background pixels in a digital image can be distinguished by their gray level values. For the segmentation of more complex images, it is necessary to resort to multiple threshold selection techniques. This paper describes a new method for multiple threshold selection of gray level images which are not clearly distinguishable from the background. The proposed method consists of three main stages. In the first stage, a probability distribution function for a gray level histogram of an image is derived. Cluster points are defined according to the probability distribution function. In the second stage, fuzzy partition matrix of the probability distribution function is generated through the fuzzy clustering process. Finally, elements of the fuzzy partition matrix are classified as clusters according to gray level values by using max-membership method. Boundary values of classified clusters are selected as multiple threshold. In order to verify the performance of the developed algorithm, automatic inspection process of ball grid array is presented.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.4
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• pp.76-82
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• 2017

The cylinder liner of a diesel engine is commonly made of gray cast iron. However, this cylinder liner can be damaged by the cavitation phenomenon in wet conditions. This cavitation has remained an unsolved problem until now. In this study, the cause of cavitation corrosion due to antifreeze solution was examined using a scanning electron microscope (SEM) and a 3D microscope. The necessary data to prevent the damage caused by cavitation erosion and the corrosion of gray cast iron cylinder liner was obtained. Analysis determined that the gray iron structure consists of an ${\alpha}-matrix$, flake graphite, and steadite. Cavitation erosion was initiated in the coarse flake graphite and propagated into the steadite with pitting. Under repetitive reaction conditions, the ${\alpha}-matrix$ was partially separated from the gray cast iron. This study is expected to be used as the basic data for the prevention of gray cast iron cavitation erosion and corrosion by controlling the graphite and steadite phases.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.130-137
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• 2018

Recently, human life is getting longer due to change of living environment and development of medical technology, and silver medical technology has been in the limelight. Geriatric skin disease is difficult to detect early, and when it is missed, it becomes a malignant disease and is difficult to treatment. Melanoma is one of the most common diseases of geriatric skin disease and initially has a similar modality with the nevus. In order to overcome this problem, we attempted to perform a feature analysis in order to attempt automatic detection of melanoma-like lesions. In this paper, one is first order analysis using information of pixels in radiomic feature. The other is a gray-level co-occurrence matrix and a gray level run length matrix, which are feature extraction methods for converting image information into a matrix. The features were extracted through these analyses. And classification is implemented by SVM.

• Proceedings of the Optical Society of Korea Conference
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• 2001.08a
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• pp.124-125
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• 2001

• Proceedings of the KOSOMBE Conference
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• v.1991 no.11
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• pp.57-60
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• 1991

A new approach to texture classification for ultrasound liver diagnosis using run difference matrix was developed. The run difference matrix consists of the gray level difference along with distance. From this run difference matrix, we defined several parameters such as LDE, LDEL, NUF, SMO, SMG, SHP etc. and three vectors namely DOD, DGD and DAD. Each parameter value calculated in fatty cirrhotic, chronic hepatitic and normal liver mage was plotted in two dimensional plane. We compared our results with run length method. There are several advantages of run difference matrix method over the run lengths. 1) It is more sensitive to small difference of gray level distribution. 2) The parameters provide more statistically significant value. Images were classified with the extracted parameters to each diseases using neural networks. In preliminary clinical exprements, this approach showed satisfying results.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.133-138
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• 2015

This paper presents a performance improvement of gray level co-occurrence matrix(GLCM) based on the nonuniform quantization, which is generally used to analyze the texture of images. The nonuniform quantization is given by Lloyd algorithm of recursive technique by minimizing the mean square error. The nonlinear intensity levels by performing nonuniformly the quantization of image have been used to decrease the dimension of GLCM, that is applied to reduce the computation loads as a results of generating the GLCM and calculating the texture parameters by using GLCM. The proposed method has been applied to 30 images of $120{\times}120$ pixels with 256-gray level for analyzing the texture by calculating the 6 parameters, such as angular second moment, contrast, variance, entropy, correlation, inverse difference moment. The experimental results show that the proposed method has a superior computation time and memory to the conventional 256-level GLCM method without performing the quantization. Especially, 16-gray level by using the nonuniform quantization has the superior performance for analyzing textures to another levels of 48, 32, 12, and 8 levels.