• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.48-52
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• 2023

Many studies have been conducted to ensure that Visual Place Recognition is reliable in various environments, including edge cases. However, existing approaches use visible imaging sensors, RGB cameras, which are greatly influenced by illumination changes, as is widely known. Thus, in this paper, we use an invisible imaging sensor, a long wave length infrared camera (LWIR) instead of RGB, that is shown to be more reliable in low-light and highly noisy conditions. In addition, although the camera sensor used to solve this problem is an LWIR camera, but since the thermal image is converted into RGB image the proposed method is highly compatible with existing algorithms and databases. We demonstrate that the proposed method outperforms the baseline method by about 0.19 for recall performance.

• Current Optics and Photonics
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• v.3 no.5
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• pp.408-414
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• 2019

In this paper we propose a method to generate a true color image in scanning white-light interferometry (SWLI). Previously, a true color image was obtained by using a color camera, or an RGB multichannel light source. Here we focused on acquiring a true color image without any hardware changes in basic SWLI, in which a monochrome camera is utilized. A Fourier transform method was used to obtain the spectral intensity distributions of the light reflected from the sample. RGB filtering was applied to the intensity distributions, to determine RGB values from the spectral intensity. Through color corrections, a true color image was generated from the RGB values. The image generated by the proposed method was verified on the basis of the RGB distance and peak signal-to-noise ratio analysis for its effectiveness.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.441-443
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• 2018

This paper deals with the analysis of leg motion using RGB image. We used RGB image as gait analysis element by using BMC(Background Model Challenge) method and by using combining object recognition segmentation algorithm and attitude detection algorithm. It is considered that gait analysis incorporating image can be used as a parameter for classification of gait pattern recognition and abnormal gait.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.457-461
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• 2013

This paper proposes an image feature-based real-time RGB-D (Red-Green-Blue Depth) 3D SLAM (Simultaneous Localization and Mapping) system. RGB-D data from Kinect style sensors contain a 2D image and per-pixel depth information. 6-DOF (Degree-of-Freedom) visual odometry is obtained through the 3D-RANSAC (RANdom SAmple Consensus) algorithm with 2D image features and depth data. For speed up extraction of features, parallel computation is performed with GPU acceleration. After a feature manager detects a loop closure, a graph-based SLAM algorithm optimizes trajectory of the sensor and builds a 3D point cloud based map.

• Journal of the Korean Graphic Arts Communication Society
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• v.27 no.1
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• pp.29-47
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• 2009

Generally, if RGB image is sent to the printer when we print a digital photograph, the printer will convert RGB to CMYK by the inner built-in drive. Because the difference between color domain of RGB and CMYK will cause that change and difference. The most common way to solve the problem is to convert colors by using ICC profile at RIP software or to adapt automatic color converting from the software of the original printer. So we intended to study show which way is most efficient to the digital output and which color mode device is the best based on the printer's own drive in this paper. we tried to observe and check the extended range of color space such as AdobeRGB as well as CMYK and sRGB. Then we made sure which is the suitable color space. Besides, When we convert RGB mode into CMYK mode by utilizing RIP software and adapt the printer's ICC profile made by our selves, we evaluated the output we get and compared the result with extended RGB image. The results are as follows. In case of RGB mode, the printer requests RGB, and that makes the color space more efficient than CMYK's. Converted to CMYK by utilizing RIP software, the chroma is more linearized than the one produced with its' own driver. Compared with sRGB mode's color gamut, AdobeRGB mode's color gamut and CMYK mode's color, CMYK mode's color gamut is the smallest among 3 of them. CMYK mode's color gamut by utilizing RIP software can be changeable. that can be small and narrow or wide and broad. In other words, the volume of color gamut depends on how CMYK is linearized. The color space of sRGB is more advantageous than the one of AdobeRGB in color-reproduction printed. But in the group $-b^*$, the chroma leaves behind in terms of reproduction, In the group of $-a^*$, the chroma is excellent relatively. Visual evaluation of the image, AdobeRGB image has not many reproduction colors. Specially, according to printers' characteristics, Group B of AdobeRGB and sRGB color space is a long way behind In terms of reproduction but Group Y is excellent relatively.

• Journal of the Semiconductor & Display Technology
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• v.13 no.4
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• pp.49-54
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• 2014

This paper proposes a new color segmentation method of vehicle license plates in the RGB color space. Firstly, the proposed method shifts the histogram of an input image rightwards and then stretches the image of the histogram slide. Secondly, the method separates each of the three RGB color components and performs the adaptive threshold processing with the three components, respectively. Finally, it combines the three components under the condition of making up a segment color and removes noises with the morphological processing. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using real vehicle images. The results show that the proposed algorithm is successful for most vehicle images. However, the method fails in some vehicles when the body and the license plate have the same color.

• Korean Journal of Bronchoesophagology
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• v.18 no.2
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• pp.45-48
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• 2012

Background Neoplastic vessels tend to proliferate on the surface of malignant lesions in the aerodigestive tract. So, superficial malignant lesions can be detected earlier by enhancing mucosal vascular clarity. To enhance mucosal vascular clarity on endoscopic image, we developed an image processing algorithm of RGB (red-green-blue) channel substitution image (CSI). Methods Each pixel in original white light image (WLI) has its own value of red, green and blue channel. Various combinations of RGB channel substitution was tried on original WLI. Results To make superficial blood vessels darker than brighter background mucosa, in the CSI algorithm, RGB value in each pixel of WLI is substituted; red value to green one, green value to blue one. There was a good contrast between superficial mucosal vessels and background brighter mucosa in the CSI image. Conclusion By RGB CSI algorithm, WLI could be successfully converted to new images with enhanced mucosal vascular clarity. Using RGB CSI algorithm could provide added vascular visibility on original WLI.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.129-134
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• 2023

The greatest challenge of this century is the protection of stored and transmitted data over the network. This paper provides a new hybrid algorithm designed based on combination algorithms, in the proposed algorithm combined with Hill and the Advanced Encryption Standard Algorithms, to increase the efficiency of color image encryption and increase the sensitivity of the key to protect the RGB image from Keyes attackers. The proposed algorithm has proven its efficiency in encryption of color images with high security and countering attacks. The strength and efficiency of combination the Hill Chipper and Advanced Encryption Standard Algorithms tested by statical analysis for RGB images histogram and correlation of RGB images before and after encryption using hill cipher and proposed algorithm and also analysis of the secret key and key space to protect the RGB image from Brute force attack. The result of combining Hill and Advanced Encryption Standard Algorithm achieved the ability to cope statistically

• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1945-1953
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• 2022

Korea Aerospace Research Institute produces mosaic images of the Korean Peninsula every year to promote the use of satellite images and provides them to users in the public sector. However, since the pan-sharpening and color balancing methodologies are applied during the mosaic image processing, the original spectral information is distorted. In addition, there is a limit to analyze using mosaic images as mosaic images provide only Red, Green and Blue bands excluding Near Infrared (NIR) band. Therefore, in order to compensate for these limitations, this study applied the Principal Component Analysis (PCA) technique and indices extracted from R, G, B bands together for image classification and compared the classification results. As a result of the analysis, the accuracy of the mosaic image classification result was about 67.51%, while the accuracy of the image classification result using both PCA and RGB indices was about 75.86%, confirming that the accuracy of the image classification result can be improved. As a result of comparing the PCA and the RGB indices, the accuracy of the image classification result was about 64.10% and 74.05% respectively. Through this, it was confirmed that the classification accuracy using the RGB indices was higher among the two techniques, and implications were derived that it was important to use high quality reference or supplementary data. In the future, additional indices and techniques are needed to improve the classification and analysis results of mosaic images, and related research is expected to increase the utilization of images that provide only R, G, B or limited spectral information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1681-1688
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• 2017

In this paper, we implemented a high-speed signal processing hardware system for Color Line Scan Camera using FPGA and Nor-Flash. The existing hardware system mainly processed by high-speed DSP based on software and it was a method of detecting defects mainly by RGB individual logic, however we suggested defect detection hardware using RGB-HSL hardware converter, FIFO, HSL Full-Color Defect Decoder and Image Frame Buffer. The defect detection hardware is composed of hardware look-up table in converting RGB to HSL and 4K HSL Full-Color Defect Decoder with high resolution. In addition, we included an image frame for comprehensive image processing based on two dimensional image by line data accumulation instead of local image processing based on line data. As a result, we can apply the implemented system to the grain sorting machine for the sorting of peanuts effectively.