• Journal of IKEEE
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• v.24 no.1
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• pp.25-32
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• 2020

In this paper, we propose an image generator for OLED panel test that can compensate for color coordinates and luminance by using panel defect inspection and optical measurement while displaying images on OLED panel. The proposed image generator consists of two processes: the image generation process and the process of compensating color coordinates and luminance using optical measurement. In the image generating process, the panel is set to receive the panel information to drive the panel, and the image is output by adjusting the output setting of the image generator according to the panel information. The output form of the image is configured by digital RGB method. The pattern generation algorithm inside the image generator outputs color and gray image data by transmitting color data to a 24-bit data line based on a synchronization signal according to the resolution of the panel. The process of compensating color coordinates and luminance using optical measurement outputs an image to an OLED panel in an image generator, and compensates for a portion where color coordinates and luminance data measured by an optical module differ from reference data. To evaluate the accuracy of the image generator for the OLED panel test proposed in this paper, Xilinx's Spartan 6 series XC6SLX25-FG484 FPGA was used and the design tool was ISE 14.5. The output of the image generation process was confirmed that the target setting value and the simulation result value for the digital RGB output using the oscilloscope matched. Compensating the color coordinates and luminance using optical measurements showed accuracy within the error rate suggested by the panel manufacturer.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.49-55
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• 2012

Pacman is one of the world-famous and have been chosen game in the game room at the arcade. In this paper, pacman game gives you the ability to perform by simple hand movement alone. First, we obtain binary RGB image to extract skin color, and convert into binary image YCbCr by minus the luminance in this image. Next, we extract the hand region by the product of an binary RGB image and binary YCbCr image. Finally, the hand region, we obtain the center of gravity by the minimum bounding rectangle and the center of the hand pixel area, and we used to obtain the center of the hand area with an average of two center of gravity. In other words, we presented the game of motion that can take the place of arrow key by using the center coordinates of hand. In addition, these experiments showed the average movement and error rate, and cause of the error type was also investigated.

• Journal of the Korean Graphic Arts Communication Society
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• v.26 no.2
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• pp.65-77
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• 2008

The color reproduction of digital still camera does not, in general, match those of the final prints. Because color gamut of these devices is different, it is therefore necessary to take account of a way to match. The way uses the optimized profile to print an image. This paper proposed a way to create the input profile of digital still camera for standardization printing process. The results of proposed way showed that for input profiles equivalent, good results relatively. In this paper, an experiment was done where the illumination sources used as the standard illumination 5200K and illuminated at a $45^{\circ}$ angle in the best illumination efficiently. The white balance was in mode 'custom': aperture F11, exposure time 1/60s, ISO50, focal length 80mm. The images were exported and saved as 16bit RGB tiff(AdobeRGB, sRGB, ProphotoRGB) images. To do the test, the RGB values of the RGB tiff images are processed through the ICC input profile to arrive at processed $CIEL^*a^*b^*$ values. A profiling tool such as ProfileMaker 5.0 and Monacoprofile 4.8 are used to do this. The processed CIEL*a*b* values are compared to the reference CIEL*a*b* values and these two values are used to calculate a ${\Delta}E$.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.67-72
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• 2012

In this paper, we present an image enhancement method for atmospherically degraded images using atmospheric light and transmission based on color analysis. We first generate a normalized image using maximum value of each RGB color channel. Then, each atmospheric light is estimated from RGB color channel respectively by calculating reflectance of an image. We also, generate a transmission using gamma coefficients from the Y channel of the image. We can significantly enhance the visibility of an image by using the estimated atmospheric light and the transmission. The proposed algorithm can remove atmospheric degradation components better than existing techniques because the color prevents color distortion which is common problem of existing techniques. Experimental results demonstrate that the proposed algorithm can improve visibility be removing fog, smoke, and dust.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.119-126
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• 2013

In this paper, we propose a chromatic aberration removal algorithm in image capture devices, which considers local properties of the image. Chromatic aberration is generated by the fact that the refractive index of the lens is different for different wavelengths, which produces color artifacts on strong edge due to misalignment of RGB channels. Under the characteristics of the artifacts, the proposed algorithm first estimates the regions with the apparent color artifacts as the neighborhoods of the strong edge. In the regions, the proposed algorithm removes the color artifacts by matching the edges of RGB channels. The widely used conventional methods based on global image warping could not remove the color artifacts of longitudinal chromatic aberration and purple fringing identified by the image sensor, whereas the matching process of the proposed method could reduce them. Experimental results show that the proposed algorithm outperforms the conventional methods on objective and subjective criteria.

• Korean Journal of Agricultural Science
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• v.47 no.2
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• pp.349-360
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• 2020

Fire-blight disease is a kind of contagious disease affecting apples, pears, and some other members of the family Rosaceae. Due to its extremely strong infectivity, once an orchard is confirmed to be infected, all of the orchards located within 100 m must be buried under the ground, and the sites are prohibited to cultivate any fruit trees for 5 years. In South Korea, fire-blight was confirmed for the first time in the Ansung area in 2015, and the infection is still being identified every year. Traditional approaches to detect fire-blight are expensive and require much time, additionally, also the inspectors have the potential to transmit the pathogen, Thus, it is necessary to develop a remote, unmanned monitoring system for fire-blight to prevent the spread of the disease. This study was conducted to detect fire-blight on pear trees using discriminant analysis with color information collected from a rotary-wing drone. The images of the infected trees were obtained at a pear orchard in Cheonan using an RGB camera attached to a rotary-wing drone at an altitude of 4 m, and also using a smart phone RGB camera on the ground. RGB and Lab color spaces and discriminant analysis were used to develop the image processing algorithm. As a result, the proposed method had an accuracy of approximately 75% although the system still requires many flaws to be improved.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.846-849
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• 2004

Compared to the bar code which is being widely used for commercial products management, color code is advantageous in both the outlook and the number of combinations. And the color code has application areas complement to the RFID's. However, due to the severe distortion of the color component values, which is easily over $50{\%}$ of the scale, color codes have difficulty in finding applications in the industry. To improve the accuracy of recognition of color codes, it'd better to statistically process an entire color region and then determine its color than to process some samples selected from the region. For this purpose, we suggest a technique to detect edges between color regions in this paper, which is indispensable for an accurate segmentation of color regions. We first transformed RGB color image to HSI and YIQ color models, and then extracted I- and Y-components from them, respectively. Then we performed Canny edge detection on each component image. Each edge image usually had some edges missing. However, since the resulting edge images were complementary, we could obtain an optimal edge image by combining them.

• Journal of the Korean Graphic Arts Communication Society
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• v.22 no.1
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• pp.9-18
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• 2004

Recently as color image processing to be become independent have been desired at the light source in an image processing and it have been enlarged. An image processing of the light source which is become independent means an image processing which uses a spectral reflectance information. We improved it in the spectral reflectance estimation method which uses existing 3-band image in this research that the improvement of an identity color population generation method which uses the hue angle and the processing speed improvement and introduces a labelling method. The precision of a spectral reflectance estimation appeared to the ${\Delta}E^*_{ab}$ of an average 2.7 comparing with the measurement price. The practical use possibility came to be fast and appeared a processing speed compared with existing method.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.1-6
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• 2018

In this paper, we propose a method dividing effectively the hand and fingers using general webcam. The method executes 4 times empirically preprocessing one to erase noise. First, it erases the overall noise of the image using Gaussian smoothing. Second, it changes from RGB image to HSV color model and YCbCr color model, executes a global static binarization based on the statistical value for each color model, and erase the noise through bitwise-OR operation. Third, it executes outline approximation and inner region filling algorithm using RDP algorithm and Flood fill algorithm and erase noise. Lastly, it erases noise through morphological operation and determines the threshold propositional to the image size and selects the hand and fingers area. This paper compares to existing one color based hand area division method and focuses the noise deduction and can be used to a gesture recognition application.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.2
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• pp.71-79
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• 2008

This study proposed a content-based image retrieval system that uses RGB maximum frequency indexing and BW clustering in order to deal with existing retrieval errors using histogram. We split RGB from RGB color images, obtained histogram which was evenly split into 32 bins, calculated and analysed pixels of each area at histogram of R, G, B and obtained the maximum value. We indexed the color information obtained, obtained 100 similar images using the values, operated the final image retrieval system using the total number and distribution rate of clusters. The algorithm proposed in this study used space information using the features obtained from R, G, and B and clusters to obtain effective features, which overcame the disadvantage of existing gray-scale algorithm that perceived different images as same if they have the same frequencies of shade. As a result of measuring the performances using Recall and Precision, this study found that the retrieval rate and priority of the proposed algorithm are more outstanding than those of existing algorithm.