• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.2
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• pp.139-146
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• 2020

The camouflage pattern was difficult to distinguish from the surrounding background, so it was difficult to classify the object and the background image when the color image is used as the training data of deep-learning. In this paper, we proposed a red-green color blindness image transformation method using the principle that people of red-green blindness distinguish green color better than ordinary people. Experimental results show that the camouflage soldier's recognition performance improved by proposed a deep learning model of the ensemble technique using the imitated red-green-blind image data and the original color image data.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11a
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• pp.328-331
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• 2001

Color simulation on a portable colorimeter was performed to distinguish quantitatively a chromaticity coordinates on a color guide of a urine strips by using the spectral power distribution of chip LED, the spectral reflectance of printed objects, and the spectral sensitivity of photodiode. The CIE tristimulus values and chromaticity coordinates realized by a colorimeter were modified to be conformable with real color reactions. Experimental results showed a real color in comparison with those obtained by Colorimeter CM2C(Color Savvy).

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11a
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• pp.320-323
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• 2001

A computer simulation was performed to distinguish quantitatively a color reaction in a urine analysis systems by using the spectral power distribution of LEDs, the spectral reflectance of a urine strip, and the spectral sensitivity of photodiode. The CIE tristimulus values and CIE chromaticity coordinates ware modified to be conformable with real color reactions in a urine strips. Results on color simulation showed a of real color in comparison with those obtained by Colorimeter CM2C(Color Savvy).

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.579-582
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• 1999

In this paper, we propose a human face detection algorithm using adaptive skin color model and neural networks. To attain robustness in the changes of illumination and variability of human skin color, we perform a color segmentation of input image by thresholding adaptively in modified hue-saturation color space (TSV). In order to distinguish faces from other segmented objects, we calculate invariant moments for each face candidate and use the multilayer perceptron neural network of backpropagation algorithm. The simulation results show superior performance for a variety of poses and relatively complex backgrounds, when compared to other existing algorithm.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.9
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• pp.1125-1137
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• 2011

This study investigates when and why the light pink Dan-ryoung appeared as part of the official uniform of the Joseon Dynasty and which official uniform used the light pink color. The Annals of the Joseon Dynasty, books written by scholars, and related laws were used as research materials. The following results were obtained by analyzing the arguments of kings and officials on light pink uniforms and laws related to official uniforms. 1. Red was the color of the king as well as the color of Dang-sang-gwan's Gong-bok (one of the official uniforms). 2. The colors such as To-hong, Dam-hong, Do-hong, Bun-hong, Cheon-hong that appeared in Sang-bok (among official uniforms) were relatively lighter than red. 3. To-hong started to be used in Sang-bok at the time of King Se-jong and was used at the time of King Seong-jong in Sang-bok because it was the preferred color. 4. In the Joseon Dynasty, safflower (the basis of red color dye) was cultivated extensively; in addition, people liked red dyeing because it was relatively easy apply; subsequently, a ban on red dyeing was continually issued. 5. Kings Se-jong and Jung-jong ordered officials to use Do-hong and Bun-hong to distinguish the red color of the king. After Im-jin-oe-ran, Cheon-hong was officially designated the color of Sang-bok. 6. The reasons why Dam-hong was used in official uniforms were twofold: the preference for red-like colors and the influence of the Confucian hierarchy to distinguish the king.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.347-350
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• 2011

This paper propose a statistical color model of background extraction base on Hue-Saturation-Value(HSV) color space, instead of the traditional RGB space, and shows that it provides a better use of the color information. HSV color space corresponds closely to the human perception of color and it has revealed more accuracy to distinguish shadows [3] [4]. The key feature of this segmentation method is based on processing hue component of color in HSV color space on image area. The HSV color model is used, its color components are efficiently analyzed and treated separately so that the proposed algorithm can adapt to different environmental illumination condition and shadows. Polar and linear statistical operations are used to calculate the background from the video frames. The experimental results show that the proposed background subtraction method can automatically segment video objects robustly and accurately in various illuminating and shadow environments.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.242-245
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• 2019

In this paper, watermark embedding technique was proposed to securely conceal the watermark in color cover image by applying the spatial encryption technique. The embedded watermak can be extracted from stego-image without loss. The quality of the stego-image is very good. So it is not possible to visually distinguish the difference between the original cover image and the stego-image. The validity of the proposed technique was verified by mathematical analysis. The proposed watermark embedding technique can be used for intellectual property protection, military, and medical applications that require high security.

• Publications of The Korean Astronomical Society
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• v.27 no.4
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• pp.293-294
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• 2012

We established a separation scheme to distinguish galaxies from stars with the aid of AKARI/FIS color-color (CC) diagrams. In all the combinations of CC diagrams we can distinguish two separate clouds. It was shown that in all cases one of them contains more than 95% of galaxies and the other one, in most cases, consists in more than 80% of stars (Pollo et al., 2010). Currently we are looking into more detailed classifications. We are especially interested in separating different morphological types of galaxies, mainly within spiral galaxies. Moreover, we study the properties of infrared galaxies.

• Journal of the Semiconductor & Display Technology
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• v.16 no.4
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• pp.79-85
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• 2017

Understanding of human emotion has a high importance in interaction between human and machine communications systems. The most expressive and valuable way to extract and recognize the human's emotion is by facial expression analysis. This paper presents and implements an automatic extraction and recognition scheme of facial expression and emotion through still image. This method has three main steps to recognize the facial emotion: (1) Detection of facial areas with skin-color method and feature maps, (2) Creation of the Bezier curve on eyemap and mouthmap, and (3) Classification and distinguish the emotion of characteristic with Hausdorff distance. To estimate the performance of the implemented system, we evaluate a success-ratio with emotional face image database, which is commonly used in the field of facial analysis. The experimental result shows average 76.1% of success to classify and distinguish the facial expression and emotion.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.383-386
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• 2002

It is very important to inspect color of printed texture in the textile process. To distinguish the color of the printed texture, RGB color values obtained from a scanner must be transformed to the standard colorimetric system used in the textile industry. It is XYZ color system that is defined by CIE(Commission Internationale do 1Eclairage). The mapping from RGB to XYZ color values is not simple and the scanner has even a positional deviation of RGB colors. In this paper an automatic color inspection method using a general scanning machine is presented. We used a U(neural network) model to map RGB to XYZ and compensate the positional error. In the real experiments, this inspection system shows to get very exact XYZ values from the traditional scanner regardless of the measuring position.