• Journal of Korea Society of Industrial Information Systems
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• v.10 no.2
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• pp.102-108
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• 2005

CIELAB coordinate is represented by one lightness component and two chromaticity components and similar to human visual system. Visual devices such as computer monitor display images using RGB coordinate. We propose a technique for inserting the watermark of visually recognizable mark into the middle frequency domain of image. RGB coordinate image is transformed into CIELAB coordinate, which include the characteristics of Human vision and then a* component is transformed into DFT(Discrete Fourier transform) transform.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.243-246
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• 2002

The proliferation of digitized media(audio, image and video) is creating a processing need for copyright enforcement schemes that protect copyright ownership. we argue that a watermark must be placed in perceptually significant components of a signal if it is to be robust to signal distortions and malicious attack. In this paper, RGB coordinate image is transformed into LUV coordinate, it include the characteristics of, Human vision and then the UV component is transformed into NxN block DCT transform. we propose a technique for embedding the watermark of visually recognizable mark into the middle frequency domain of image.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.2
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• pp.65-70
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• 2013

In this paper, we proposed color image watermarking using human visual system. A watermark is embedded by transforming a color image of RGB coordinate into a color image of HSI coordinate with considering that chromatic components are less sensitive than achromatic components. Watermark is embedded in the frequency domain of the chromatic channels by using discrete cosine transform. Watermark is extracted from watermarked image by using inverse discrete cosine transform. To verify the proposed method, a standard image and a fingerprint image are used for the original image and the watermark image, respectively. Simulation results are satisfied with invisibility and robustness from attacks as image compression.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.765-774
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• 2019

In this paper, we propose a point cloud matching algorithm for multiple RGB-D cameras. In general, computer vision is concerned with the problem of precisely estimating camera position. Existing 3D model generation methods require a large number of cameras or expensive 3D cameras. In addition, the conventional method of obtaining the camera external parameters through the two-dimensional image has a large estimation error. In this paper, we propose a method to obtain coordinate transformation parameters with an error within a valid range by using depth image and function optimization method to generate omni-directional three-dimensional model using 8 low-cost RGB-D cameras.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.309-314
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• 2014

To generate a complete 3D model from depth images of multiple RGB-D cameras, it is necessary to find 3D transformations between RGB-D cameras. This paper proposes a convenient view calibration technique using a spherical object. Conventional view calibration methods use either planar checkerboards or 3D objects with coded-pattern. In these conventional methods, detection and matching of pattern features and codes takes a significant time. In this paper, we propose a convenient view calibration method using both 3D depth and 2D texture images of a spherical object simultaneously. First, while moving the spherical object freely in the modeling space, depth and texture images of the object are acquired from all RGB-D camera simultaneously. Then, the external parameters of each RGB-D camera is calibrated so that the coordinates of the sphere center coincide in the world coordinate system.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.1
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• pp.1-8
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• 2011

In this paper, the method to calculate chromaticity coordinate from spectral power distribution of LED is presented. Also, inverse tri-stimulus algorithm to find mixed luminance of red, green, blue LED from targeted luminance and chromaticity coordinate is proposed. Besides, digital light color control system of LED lamp applied this algorithm has been developed. In experiments, each chromaticity coordinate of red, green, blue LED calculated from this algorithm has relative percentage error of few % to measured values. Digital code is drawn from inverse tri-stimulus algorithm, and measured values of luminance and chromaticity coordinate of LED lamp digitally controlled by this code also have relative percentage error within a few % to targeted luminance and chromaticity coordinate.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.439-448
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• 2020

In this paper, we propose a modified optimization algorithm for point cloud matching of multi-view RGB-D cameras. In general, in the computer vision field, it is very important to accurately estimate the position of the camera. The 3D model generation methods proposed in the previous research require a large number of cameras or expensive 3D cameras. Also, the methods of obtaining the external parameters of the camera through the 2D image have a large error. In this paper, we propose a matching technique for generating a 3D point cloud and mesh model that can provide omnidirectional free viewpoint using 8 low-cost RGB-D cameras. We propose a method that uses a depth map-based function optimization method with RGB images and obtains coordinate transformation parameters that can generate a high-quality 3D model without obtaining initial parameters.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.4
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• pp.227-233
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• 2013

In this paper, we propose an implementation of pH reader on Android smart phone by using Eclipse and SDK. After taking a picture of pH spectrum and tested litmus paper at the same time, we save the picture. From the picture, reference values in RGB and YUB of all pH color in the spectrum are obtained and then those of a chosen point by user in the litmus paper are to be compared with. The distances between the reference colors and the litmus paper's color are measured by Euclidean distance in RGB or YUB coordinate. The nearest two pH values are taken to find the weighted average of the result. Series of test show the proposed scheme is feasible and has performance within 10% error.

• Journal of Korean Ophthalmic Optics Society
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• v.10 no.1
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• pp.1-8
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• 2005

Color vision of color vision deficiency is possible using Color space's conversion of color image. Color vision of the RG-Color vision deficiency is possible by the case to maximize the G channel(+100), the case to minimize the G channel(-100), the case to maximize the R channel(+100), the case to convert the R channel to the yellow(Y) channel that is the value of $(-)b^*$ coordinate in CIE $L^*a^*b^*$ color space, the case to separate with only the B channel and the G channel and to appear by the light and darkness difference again, and the case to receive the image only by the light and darkness after separation of saturation and conversion of RGB channel.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.72-77
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• 2023

In many manufacturing settings, including the semiconductor industry, products are completed by producing and assembling various components. Sorting out from randomly mixed parts and classification operations takes a lot of time and labor. Recently, many efforts have been made to select and assemble correct parts from mixed parts using robots. Automating the sorting and classification of randomly mixed components is difficult since various objects and the positions and attitudes of robots and cameras in 3D space need to be known. Previously, only objects in specific positions were grasped by robots or people sorting items directly. To enable robots to pick up random objects in 3D space, bin picking technology is required. To realize bin picking technology, it is essential to understand the coordinate system information between the robot, the grasping target object, and the camera. Calibration work to understand the coordinate system information between them is necessary to grasp the object recognized by the camera. It is difficult to restore the depth value of 2D images when 3D restoration is performed, which is necessary for bin picking technology. In this paper, we propose to use depth information of RGB-D camera for Z value in rotation and movement conversion used in calibration. Proceed with camera calibration for accurate coordinate system conversion of objects in 2D images, and proceed with calibration of robot and camera. We proved the effectiveness of the proposed method through accuracy evaluations for camera calibration and calibration between robots and cameras.