• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.173-188
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• 2005

The present study aims to derive and compare narrow and broad bandwidths of ocean color sensor’s algorithms for the study of monitoring highly dynamic coastal oceanic environmental parameters using high-resolution imagery acquired from Multi-spectral Camera (MSC) on KOMPSAT-2. These algorithms are derived based on a large data set of remote sensing reflectances ($R_{rs}$) generated by using numerical model that relates $b_b/(a + b_b)$ to $R_{rs}$ as functions of inherent optical properties, such as absorption and backscattering coefficients of six water components including water, phytoplankton (chl), dissolved organic matter (DOM), suspended sediment (SS) concentration, heterotropic organism (he) and an unknown component, possibly represented by bubbles or other particulates unrelated to the first five components. The modeled $R_{rs}$ spectra appear to be consistent with in-situ spectra collected from Korean waters. As Kompsat-2 MSC has similar spectral characteristics with Landsat-5 Thematic Mapper (TM), the model generated $R_{rs}$ values at 2 ㎚ interval are converted to the equivalent remote sensing reflectances at MSC and TM bands. The empirical relationships between the spectral ratios of modeled $R_{rs}$ and chlorophyll concentrations are established in order to derive algorithms for both TM and MSC. Similarly, algorithms are obtained by relating a single band reflectance (band 2) to the suspended sediment concentrations. These algorithms derived by taking into account the narrow and broad spectral bandwidths are compared and assessed. Findings suggest that there was less difference between the broad and narrow band relationships, and the determination coefficient $(r^2)$ for log-transformed data [ N = 500] was interestingly found to be $(r^2)$ = 0.90 for both TM and MSC. Similarly, the determination coefficient for log-transformed data [ N = 500] was 0.93 and 0.92 for TM and MSC respectively. The algorithms presented here are expected to make significant contribution to the enhanced understanding of coastal oceanic environmental parameters using Multi-spectral Camera.

• Applied Chemistry for Engineering
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• v.30 no.4
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• pp.421-428
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• 2019

This paper describes a methode to extract yellow pigment from curcuma and turmeric containing natural color curcumin whose target color indexes of L, a, and b were 87.0 7.43, and 88.2, respectively. The pH range and extraction temperature used for the reaction surface analysis method were from pH 3 to pH 7 and between 40 and $70^{\circ}C$, respectively for both natural products. A central synthesis planning model combined with the method was used to obtain optimal extraction conditions to produce the color close to target. Results and regression equations show that the color space and difference of curcuma and turmeric have the greatest influence on the value. In the case of curcuma, the optimum conditions to satisfy all of the response theoretical values of color coordinates of L (74.67), a (5.69), and b (70.08) were at the pH and temperature of 3.43 and $54.8^{\circ}C$, respectively. The experimentally obtained L, a, and b, values under optimal conditions were 72.92, 5.32, and 72.17, respectively. For the case of turmeric, theoretical numerical color coordinates of L, a, and b, under the pH of 5.22 and temperature of $50.4^{\circ}C$ were 82.02, 7.43, and 72.86 respectively. Whereas, the experiment results were L (81.85), a (5.39), and b (71.58). Both cases showed an error range within 1%. Therefore, it is possible to obtain a low error rate when applying the central synthesis planning model to the reaction surface analysis method as an optimization process of the dye extraction of natural raw materials.

• The Journal of Korean Academy of Prosthodontics
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• v.43 no.5
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• pp.587-598
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• 2005

Statement of problem: Ceramic restorations should be made of porcelain layers of different opacity, shade, and thickness in order to provide a natural appearance. Lithium disilicate glass-ceramic system has superior color reproducibility, because it uses the ceramic ingot which is similar to teeth shade and uses the staining technique and layering technique. However, staining technique has a fault of discoloration. Also, porcelain is divided core and dentin layer, it is not enough to study about the influence of porcelain layer thickness and shade on the shade of ceramic restorations. Purpose: The purpose of this study was to evaluate the influence of porcelain layer thickness and color on the final shade of ceramic restorations. Materials and method: The CIE $L^*a^*b^*$(CIELAB) values of 72 assembled specimens, each consisting of 3 discs (enamel porcelain 0.2 mm/dentin porcelain -1.2, 0.9, 0.7, 0.5 or 0.3 mm/ceramic core -0.3, 0.5, 0.7, 0.9 or 1.2 mm, diameter is 1.0 mm) were evaluated with a spectrophotometer (Model Chromaview 300, Spectron Tech Co, Korea) for the shade A1, A2, A3 and A4. Distilled water (refractive index: 1.7) was used to attain optical contact between the layers. White, white gray, and white brown backgrounds were used to assess the influence of the background on the final shade. And the mean color difference value$({\Delta}E)$ was calculated. Results and conclusion: The results obtained from this study were as follows. 1. There was a significant correlation between the thickness ratio of the ceramic core/dentin porcelain system and $L^*,\;a^*\;and\;b^*$ values when the total thickness of specimen combination was smaller than 1.4 mm(P<0.05). 2. The specimen which the ceramic core thickness was more than 0.7 mm had the best masking effect against background colors. 3. The mean color difference value$({\Delta}E)$ is smaller than 2 $({\Delta}E<2)$ when the ceramic core thickness was larger than 0.7 mm and the total thickness of specimen was more than 1.4 mm.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1096-1100
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• 2010

In this paper, we propose an automatic segmentation of the meniscus based on active shape model using interpolated shape information in MR images. First, the statistical shape model of meniscus is constructed to reflect the shape variation in the training set. Second, the generation technique of interpolated shape information by using the weight according to shape similarity is proposed to robustly segment the meniscus with large variation. Finally, the automatic meniscus segmentation is performed through the active shape model fitting. For the evaluation of our method, we performed the visual inspection, accuracy measure and processing time. For accuracy evaluation, the average distance difference between automatic segmentation and semi-automatic segmentation are calculated and visualized by color-coded mapping. Experimental results show that the average distance difference was $0.54{\pm}0.16mm$ in medial meniscus and $0.73{\pm}0.39mm$ in lateral meniscus. The total processing time was 4.87 seconds on average.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.12
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• pp.168-175
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• 2013

Color consistency in stereoscopic contents is important for 3D display systems. Even with a stereo camera of the same model and with the same hardware settings, complex color discrepancies occur when acquiring high quality stereo images. In this paper, we propose an integrated color matching method that use cumulative histogram in global matching and estimated 3D-distance for the stage of local matching. The distance between the current pixel and the target local region is computed using depth information and the spatial distance in the 2D image plane. The 3D-distance is then used to determine the similarity between the current pixel and the target local region. The overall algorithm is described as follow; First, the cumulative histogram matching is introduced for reducing global color discrepancies. Then, the proposed local color matching is established for reducing local discrepancies. Finally, a weight-based combination of global and local matching is computed. Experimental results show the proposed algorithm has improved global and local error correction performance for stereoscopic contents with respect to other approaches.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.35-46
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• 2007

This paper proposes a six-color separation method of reducing unnecessary usage of colorants based on the limitation of total colorant amount and dot visibility ordering. First, the CIELAB values of input RGB image are estimated through the color-mixing model and compared with pre-calculated CIELAB values corresponding to all combination of CMYKlclm colorants with a constraint of color difference, thereby selecting initial CMYKlclm candidates. Next, the limitation on total colorant amount Is imposed on initial CMYKlclm candidates to remove the excessive amounts of colorants, and then final CMYKlclm candidates are determined by minimizing the usage of light cyan and light magenta in the dark region based on the dot visibility ordering of C, M, Y, K, lc, and lm. Through the experiment, the proposed method is shown to reduce the excessive amount of colorants with preserving good image quality.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.41-46
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• 2023

Human urine is a process of excreting waste products in the blood, and it is easy to collect and contains various substances. Urinalysis is used to check for diseases, health conditions, and urinary tract infections. There are three methods of urinalysis: physical property test, chemical test, and microscopic test, and chemical test results can be easily confirmed using urine test strips. A variety of items can be tested on the urine test strip, through which various diseases can be identified. Recently, with the spread of smart phones, research on reading urine test strips using smart phones is being conducted. There is a method of detecting and reading the color change of a urine test strip using a smartphone. This method uses the RGB values and the color difference formula to discriminate. However, there is a problem in that accuracy is lowered due to various environmental factors. This paper applies a deep learning model to solve this problem. In particular, color discrimination of a urine test strip is improved in a smartphone using a lightweight CNN (Convolutional Neural Networks) model. CNN is a useful model for image recognition and pattern finding, and a lightweight version is also available. Through this, it is possible to operate a deep learning model on a smartphone and extract accurate urine test results. Urine test strips were taken in various environments to prepare deep learning model training images, and a urine test service application was designed using MobileNet V3.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.16-22
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• 2011

This paper presents the multi-object tracking approach using the background difference and particle filtering by monte carlo sampling. We apply particle filters based on probabilistic importance sampling to multi-object independently. We formulate the object observation model by the histogram distribution using color information and the object dynaminc model for the object motion information. Our approach does not increase computational complexity and derive stable performance. We implement the whole Bayesian maximum likelihood framework and describes robust methods coping with the real-world object tracking situation by the observation and transition model.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1053-1056
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• 2008

An application of CSG (Constructive Solid Geometry) modeling technique in Machining Simulation is introduced in this paper. The current CSG model is based on z-buffer CSG Rendering Algorithm. In order to build a CSG model, frame buffers of VGA (Video Graphic Accelerator) should be used in term of color buffer, depth buffer, and stencil buffer. In addition to using CSG model in machine simulation Stock and Cutter Swept Surface (CSS) should be solid. Method to create a solid Cuboid stock and Ball-end mill CSS are included in the present paper. Boolean operations are used to produce the after-cut part, especially the Difference operation between Stock and CSS as the cutter remove materials form stock. Finally, a small program called MaSim which simulates one simple cut using this method was created.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.809-816
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• 2014

Ocean Color products have been used to understand marine ecosystem. In high latitude region, ice melting optically influences the ocean color products. In this study, we assessed optical properties in fjord around Svalbard Arctic sea, and estimated distribution of chlorophyll-a and suspended sediment by using high resolution satellite data, Landsat-8 Operational Land Imager (OLI). To estimate chlorophyll-a and suspended sediment concentrations, various regression models were tested with different band ratio. The regression models were not shown high correlation because of temporal difference between satellite data and in-situ data. However, model-derived distribution of ocean color products from OLI showed a possibility that fjord and coastal areas around Arctic Sea can be monitored with high resolution satellite data. To understand climate change pattern around Arctic Sea, we need to understand ice meting influences on marine ecosystem change. Results of this study will be used to high resolution monitoring of ice melting and its influences on the marine ecosystem change at high latitude. KOPRI (Korea Polar Research Institute) has been operated the Dasan station on Svalbard since 2002, and study was conducted using Arctic station.