• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.363-366
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• 2001

The present process of grading leather quality by the rare eyes is not reliable. Because inconsistency of grading due to eyes strain for long time can cause incorrect result of grading. Therefore it is necessary to automate the process of grading quality of leather based on objective standard for it. In this paper, leather automatic classification system consists of the process obtaining the information of leather and the process grading the quality of leather from the information. Leather is graded by its information such as texture density, types and distribution of defects. This paper proposes the algorithm which sorts out leather information like texture density and defects from the gray-level images obtained by digital camera. The density information is sorted out by the distribution value of Fourier spectrum which comes out after original image is converted to the image in frequency domain. And the defect information is obtained by the statistics of pixels which is relevant to Window using searching Window after sort out boundary lines from preprocessed images. The information for entire leather is used as standard of grading leather quality, and the proposed algorithm is practically applied to machine vision system.

• Journal of Biomedical Engineering Research
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• v.19 no.2
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• pp.113-118
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• 1998

By their rapid and periodic actions, the cilia of the human respiratory tract play an important role in clearing inhaled noxious particles. Based on the automated image-processing technique, we studied the method analyzing ciliary beat frequency (CBF) objectively and quantitatively. Microscopic ciliary images were transformed into digitized gray ones through an image-grabber, and from these we extracted signals for CBF. By means of a FFT, maximum peak frequencies were detected as CBFs in each partitioned block for the entire digitized field. With these CBFs, we composed distribution maps visually showing the spatial distribution of CBFs. Through distribution maps of CBF, the whole aspects of CBF changes for cells and the difference of CBF of neighboring cells can be easily measured and detected. Histogram statistics calculated from the user-defined polygonal window can show the local dominant frequency presumed to be the CBF of a cell or a crust the region includes.

• Journal of the Korean Society of Radiology
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• v.9 no.4
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• pp.227-234
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• 2015

In this paper, we studied possibility about application for CAD on diffuse liver disease through pixel texture analysis parameters(average gray level, skewness, entropy) which based statistical property brightness histogram and image analysis using brightness difference liver and kidney parenchyma. The experiment was set by ROI ($50{\times}50$ pixels) on liver ultrasound images.(non specific, fatty liver, liver cirrhosis) then, evaluated disease recognition rates using 4 types pixel texture analysis parameters and brightness gap liver and kidney parenchyma. As a results, disease recognition rates which contained average brightness, skewness, uniformity, entropy was scored 100%~96%, they were high. In brightness gap between liver and kidney parenchyma, non specific was $-1.129{\pm}12.410$ fatty liver was $33.182{\pm}11.826$, these were shown significantly difference, but liver cirrhosis was $-1.668{\pm}10.081$, that was somewhat small difference with non specific case. Consequently, pixel texture analysis parameter which scored high disease recognition rates and CAD which used brightness difference of parenchyma are very useful for detecting diffuse liver disease as well as these are possible to use clinical technique and minimize reading miss. Also, it helps to suggest correct diagnose and treatment.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.31 no.3
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• pp.229-236
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• 2009

Purpose: Some recent literatures report that it is possible to recover defected areas caused by enucleation of relatively large jaw cysts without using bone grafts. The aim was to find out whether spontaneous recovery of defected area with time occurred and what the contributing factors were. Materials and methods: In total, 194 patients were considered as patients. Out of these 194 patients, 74 patients who had no wound dehiscence and who were available for follow-up studies were selected. They were classified into two groups according to the size of radiolucent area in the preoperative panoramic radiographs: in one group, it was larger than $3{\times}4cm$, while in the other group, it was smaller than $3{\times}4cm$. Follow-up panoramic radiographs were taken immediately after the surgery, then after 3, 6, 9 and 12 months. On those radiographs, changes in size and density of the defected areas were observed using the Gray-level histogram of Adobe photoshop v7.0. Correlation between bone regeneration and factors such as the type and size of the cysts, age, sex, site of the cysts and systemic disease was evaluated using the General repeated measure and Mann-Whitney Test. Results: Analyses of panoramic radiographs showed that the recovery of radiopacity after 12 months was more than 97% on average in defected areas that were smaller than $3{\times}4cm$. in the defected areas that were larger than $3{\times}4cm$, considerable portion showed recovery of radiopacity. No statistically significant change was observed in bone density according to the type of cysts. Young patients under 20 years of age with highly active metabolism presented more significant bone regeneration than patients over 20 years of age. Bone regeneration was more hampered in patients who had medical disease, compared with patients who didn’t have any medical problem. No statistically significant change was seen in bone density according to sex. Changes in bone density according to the site of cysts such as maxilla, mandible, anterior or posterior region were not considered to be significant. Conclusion: Analyses of panoramic radiographs suggest that in approximately 12 months after the enucleation of cysts, clinically acceptable spontaneous bone regeneration can be observed even though normal bone graft procedures have not been applied.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.32 no.5
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• pp.389-395
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• 2010

Purpose: Although it is generally accepted that patients with controlled diabetes have similar rates of success for dental implants as healthy individuals, the use of dental implants in diabetic patients is controversial. In addition, the impact of diabetes on the healing of bone associated with immediately place dental implants is not completely understood. The purpose of this study was to measure bone response to implants radiologically in uncontrolled and insulin-controlled diabetic rats. Materials and Methods: Twenty rats were divided into control, insulin-treated and diabetic groups. The rats received streptozotocin (60 mg/kg) to induce diabetes; animals in the insulin-treated group also received three units of subcutaneous slow-release insulin. Two titanium implants ($1.2{\times}3$ mm) were placed in the extraction socket of the maxillary first molars of the animals and were harvested at 3 days, 1, 2 and 4 weeks. The bone density was measured by digital radiography using gray-level analysis (histogram) in the regions of interest (ROI) at four points: two mesial and two distal to both sides of the implant. Results: The results showed that the osseointegration of the implants was impaired in the diabetic rats compared to the control and the insulin-treated rats. The radiographic evidence demonstrated marked destruction of bone around the implants in the diabetic group. Both the control and the insulin-treated groups had a significantly higher bone density on radiograph than the diabetic group from the 1 week of the experiment (P<0.05 for each comparison). Conclusion: The present study revealed that the immediate placement of titanium implants in the maxilla of diabetic rat lead to delay in the maturation of bone adjacent to implants. It is expected that the reduced predictability of success of immediate implantation in patient with the uncontrolled diabetes.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.1-10
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• 2005

Content-based image retrieval systems are being actively investigated owing to their ability to retrieve images based on the actual visual content rather than by manually associated textual descriptions. In this paper, we propose a novel approach for image retrieval based on edge structural features using edge correlogram and color coherence vector. After color vector angle is applied in the pre-processing stage, an image is divided into two image parts (high frequency image and low frequency image). In low frequency image, the global color distribution of smooth pixels is extracted by color coherence vector, thereby incorporating spatial information into the proposed color descriptor. Meanwhile, in high frequency image, the distribution of the gray pairs at an edge is extracted by edge correlogram. Since the proposed algorithm includes the spatial and edge information between colors, it can robustly reduce the effect of the significant change in appearance and shape in image analysis. The proposed method provides a simple and flexible description for the image with complex scene in terms of structural features of the image contents. Experimental evidence suggests that our algorithm outperforms the recently histogram refinement methods for image indexing and retrieval. To index the multidimensional feature vectors, we use R*-tree structure.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.5
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• pp.323-330
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• 2023

The development of an analysis model that reflects the microstructure characteristics of polyvinyl alcohol (PVA) fiber-reinforced cementitious composites, which have a highly complex microstructure, enables synergy between efficient material design and real experiments. PVA fiber orientations are an important factor that influences the mechanical behavior of PVA fiber-reinforced cementitious composites. Owing to the difficulty in distinguishing the gray level value obtained from micro-CT images of PVA fibers from adjacent phases, fiber segmentation is time-consuming work. In this study, a micro-CT test with a voxel size of 0.65 ㎛³ was performed to investigate the three-dimensional distribution of fibers. To segment the fibers and generate training data, histogram, morphology, and gradient-based phase-segmentation methods were used. A U-net model was proposed to segment fibers from micro-CT images of PVA fiber-reinforced cementitious composites. Data augmentation was applied to increase the accuracy of the training, using a total of 1024 images as training data. The performance of the model was evaluated using accuracy, precision, recall, and F1 score. The trained model achieved a high fiber segmentation performance and efficiency, and the approach can be applied to other specimens as well.