• Journal of Institute of Control, Robotics and Systems
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• v.9 no.10
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• pp.774-781
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• 2003

The important factors that cause position error in X-Y robot are inertial force, frictions and spring distortion in screw or coupling. We have to estimate these factors precisely to correct position errors, Which is very difficult. In this paper, we makes systems to inspect metal stencil which is used to print solder paste on pads of SMD of PCB with low precision X-Y robot and vision system. To correct position error that is caused by low precision X-Y robot, we defines position error vector that is formed with position of objects that exist in reference and camera image. We apply MHT(Modified Hough Transformation) for the aim of determining the dominant position error vector. We modify reference image using extracted dominant position error vector and obtain reference image that is the same with camera image. Effectiveness and performance of this method are verified by simulation and experiment.

• Journal of Biomedical Engineering Research
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• v.30 no.1
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• pp.34-40
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• 2009

Transforms including translation and rotation are required for registering two or more images. In medical applications, different registration methods have been applied depending on the structures: for rigid bodies such as bone structures, affine transformation was widely used. In most previous research, a single transform was used for registering the whole images, which resulted in low registration accuracy especially when the degree of deformation was high between two images. In this paper, a novel registration method is introduced which is based image sub-division and bilinear interpolation of transformations. The proposed method enhanced the registration accuracy by 40% comparing with Trimmed ICP for registering color and MRI images.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.124-130
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• 1996

A compensation method of color error resulting from dynamic range transformation of color image is propsoed. The color error is measured using the CIE L a b uniform color space, and the color image is compensated to minimize it. The color error is significant in the dark region of image, which is caused by the lunimance scaling factor is relatively large in that case. In the proposed method, we weight the luminance scaling factor corresponding to luminnce to minimize the error. Because the weighting factor depends on luminace distribution of image, a decisio method of weighting factor using histogram is also proposed.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.705-708
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• 2005

Mobile Mapping Systems using the vehicle equipped the GPS, IMU, CCD Cameras is the effective system for the management of the road facilities, update of the digital map, and etc. They must provide users with the sensor data which is acquired by Mobile Mapping Systems in real-time so that users can process what they want by using the latest data. But it' s not an easy process because the amount of sensor data is very large, particularly image data to be transmitted. So it is necessary to reduce the amount of image data so that it is transmitted effectively. In this study, the effective method was suggested for the compression/decompression image data using the Wavelet Transformation and Huffman Coding. This technique will be possible to transmit of the geographic information effectively such as position data, attitude data, and image data acquired by Mobile Mapping Systems in the wireless internet environment when data is transmitted in real-time.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.1
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• pp.193-200
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• 2003

This paper proposes a novel algorithm to recognize the curve of a structured road. The proposed algorithm uses an LCF (Lane Curve Function) obtained by the transformation of a parabolic function defined on world coordinate into image coordinate. Unlike other existing methods, the algorithm needs no transformation between world coordinate and image coordinate owing to the LCF. In order to search for an LCF describing the lane best, the differential comparison between the slope of an assumed LCF and the phase angle of edge pixels in the LROI (Lane Region Of Interest) constructed by the LCF is implemented. As finding the true LCF, the lane curve is determined. The proposed method is proved to be efficient through various kinds of images, providing the reliable curve direction and the valid curvature compared to the real road.

• Journal of Electrical Engineering and information Science
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• v.3 no.3
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• pp.330-335
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• 1998

In this paper, a new light-value approaching method to enhance a color image by excluding the effect of incident illumination is proposed. The method uses the fundamental vector transformation in which an estimated color of illumination is rotated to the white color of natural daylight. Then the transformed red, green, and blue values of each pixel are nonlinearly mapped into the 8-bit values to enhance intensity and saturation in the dark portion of the image. The proposed algorithm can produce the enhanced color image fast and efficiently without any space conversion or noticeable distortion.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.99-108
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• 1994

In this paper an image compression technique based on fractal theory using iterated contractive transformation is analysed and an improved image coder is suggested. Existing methods used the classifier proposed by Ramamurthi and Gersho which utilize the properties of neighboring pixels in the spatial domain. In this paper DCT-based classification is applied to 512$\times$512 images and PSNR improvement of 0.4~2.7 dB is obtained at lower bit rate over conventional algorithms. In addition the effect of varying the domain block size and quantization step size of the luminance shift parameter on the compression ratio and the image quality is compared and analysed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.1041-1046
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• 2009

In this paper, we proposed a robust watermark scheme for image based on SVD(Singular Value Transform) and Triplet. First, the original image is decomposed by using 3-level DWT, and then used the singular values changed for embedding and extracting of the watermark sequence in LL3 band. Since the matrix of singular values is not easily altered with various signal processing noises, the embedded watermark sequence has the ability to withstand various signal processing noise attacks. Nevertheless, this method does not guarantee geometric transformation(such as rotation, cropping, etc.) because the geometric transformation changes the matrix size. In this case, the watermark sequence cannot be extracted. To compensate for the above weaknesses, a method which uses the triplet for embedding a barcode image watermark in the middle of frequency band is proposed. In order to generate the barcode image watermark, the pattern of the watermark sequence embedded in a LL3 band is used. According to this method, the watermark information can be extracted from attacked images.

• Korean Institute of Interior Design Journal
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• v.15 no.1 s.54
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• pp.71-78
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• 2006

This study aims to understand the meaning of 'wall' and spatial image transformation by the wall. To find the meaning of wall, some classical works and modern works - Le Corbusier's Domino system and Schroder House-are analyzed into functional aspect of wall, in result we know that wall has of evolved throughout history to become an Increasingly active component of our built environment. Whereas the wall permits variations in the human and natural environment, the wall could be changed a lot of different shapes. The results of this study are as follows; (1) Applying new attempt to the wall makes interactivity in spatial elements. (2) Through rotation of the wall, we find the periodicity of wall length with sine curve. (3) Wall made by points and linear elements can change the spatial image, because of there geometrical characteristics.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.497-500
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• 2022

High-quality images and videos are being generated as technologies for deep learning-based image style translation and conversion of static images into dynamic images have developed. However, it takes a lot of time and resources to manually transform images, as well as professional knowledge due to the difficulty of natural image transformation. Therefore, in this paper, we study natural style mixing through a style conversion network using GAN and natural dynamic image generation using the First Order Motion Model network (FOMM).