• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.5
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• pp.73-82
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• 1996

In this paper, an efficient algorithm for recognizing and positioning occuluded objects in a two-dimensional plane is presented. Model objects and unknown input image are approximated by polygonal boundaries, which are compactly represented by shape functions of the polygons. The input image is partitioned into measningful segments whose end points are at the locations of possible occlusion - i.e. at concave vertices. Each segment is matched against known model objects by calculating a matching measure, which is defined as the minimum euclidean distance between the shape functions. An O(mm(n+m) algorithm for computing the measure is presentd, where n and m are the number of veritces for a model and an unknown object, respectively. Match results from aprtial segments are combined based on mutual compatibility, then are verified using distance transformation and translation vector to produce the final recognition. The proposed algorithm is invariant under translation and rotation of objects, which has been shown by experimental results.

• The KIPS Transactions:PartB
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• v.18B no.2
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• pp.51-56
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• 2011

Algorithms for intrinsic images reduce color differences in RGB images caused by the temperature of black-body radiators. Based on the reference light and detecting single invariant direction, these algorithms are weak in real images which can have multiple invariant directions when the scene illuminant is a colored illuminant. To solve these problems, this paper proposes a method of acquiring an intrinsic image by omnidirectional projection of an ROI and a translation of white patch in the ${\chi}$-chromaticity space. Because it is not easy to analyze an image in the three-dimensional RGB space, the ${\chi}$-chromaticity is also employed without the brightness factor in this paper. After the effect of the colored illuminant is decreased by a translation of white patch, an invariant direction is detected by omnidirectional projection of an ROI in this chromaticity space. In case the RGB image has multiple invariant directions, only one ROI is selected with the bin, which has the highest frequency in 3D histogram. And then the two operations, projection and inverse transformation, make intrinsic image acquired. In the experiments, test images were four datasets presented by Ebner and evaluation methods was the follows: standard deviation of the invariant direction, the constancy measure, the color space measure and the color constancy measure. The experimental results showed that the proposed method had lower standard deviation than the entropy, that its performance was two times higher than the compared algorithm.

• Journal of Broadcast Engineering
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• v.1 no.1
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• pp.74-83
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• 1996

In this paper, an effective color image retrieval algorithm is proposed based on the graph representation. Also we propose a color constancy algorithm to remove the effect of illumination change. Illumination condition of an image can be transformed to that of reference image using the proposed color constancy algorithm, so that the effect of dirrerent lighting is significantly alleviated. Then, we represent a color image as a graph with several nodes and edges in the histogram space, and finally two images are matched by compared two graphs representing them. The simulation results show that the proposed 3-step algorithm performs well for various conditions, including different lighting, translation, rotation, and scaling of the object in the image. In addition, the proposed algorithm is very fast compared to the geometry-based matching technique.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.452-472
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• 2019

Most existing wavelet-based multiplicative watermarking methods are affected by geometric attacks to a certain extent. A serious limitation of wavelet-based multiplicative watermarking is its sensitivity to rotation, scaling, and translation. In this study, we propose an image watermarking method by using dual-tree complex wavelet transform with a multi-objective optimization approach. We embed the watermark information into an image region with a high entropy value via a multiplicative strategy. The major contribution of this work is that the trade-off between imperceptibility and robustness is simply solved by using the multi-objective optimization approach, which applies the watermark error probability and an image quality metric to establish a multi-objective optimization function. In this manner, the optimal embedding factor obtained by solving the multi-objective function effectively controls watermark strength. For watermark decoding, we adopt a maximum likelihood decision criterion. Finally, we evaluate the performance of the proposed method by conducting simulations on benchmark test images. Experiment results demonstrate the imperceptibility of the proposed method and its robustness against various attacks, including additive white Gaussian noise, JPEG compression, scaling, rotation, and combined attacks.

• Annual Conference of KIPS
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• 2019.05a
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• pp.415-418
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• 2019

본 논문에서 grayscale 이미지를 그럴듯한 컬러 이미지로의 전환을 다루고자 한다. 기존의 CNN Network 를 통해 실제 Image 를 만들어내려는 기법들은 모든 Pixel 의 Error 를 Loss 로 사용한다. 각 픽셀별로 가장 완벽한 답을 찾으려고 하기보다는, 전체 픽셀의 관점에서의 Loss 를 줄이려고 하기 때문에, 픽셀 값이 정확한 값대신 안전한 값으로 넘어간다는 단점이 있다. 이 문제를 해결하기 위해 본 논문에서 GAN 기반의 Image-to-Image Translation 기법에 NIN(Network in Network) 적용해 이 문제를 해결할 수 있음을 보인다. 전통 CNN 기법보다 더 Photo-realistic 한 이미지를 생성할 수 있게 된다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.11
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• pp.92-102
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• 1990

A new method for determining the motion parameters (scale, rotation, translation) of 2-D image is introduced. It employs Hough transform that maps the straight lines in the input image to the points in the Hough space (HS). This method makes use of the relations between the motion of an object in input image and the translations of peak points in the HS and thus derives relating equations about motion parameters especially when scale changes are involved. The derived equations make is efficient and simple to estimate motion parameters of input image, even if the scale parameter of input image is varied. Performance of this approach on an aircraft image is provided in detail in the presence of noise.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.125-132
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• 2024

Optical satellite images are being used for national security and collection of information, and their utilization is increasing. However, it acquires low-quality images that are not suitable for the user's requirement due to weather conditions and time constraints. In this paper, a deep learning-based conversion of image and colorization model referring to high-resolution SAR images was created to simulate the occluded area with clouds of optical satellite images. The model was experimented according to the type of algorithm applied and input data, and each simulated images was compared and analyzed. In particular, the amount of pixel value information between the input black-and-white image and the SAR image was similarly constructed to overcome the problem caused by the relatively lack of color information. As a result of the experiment, the histogram distribution of the simulated image learned with the Gray-scale image and the high-resolution SAR image was relatively similar to the original image. In addition, the RMSE value was about 6.9827 and the PSNR value was about 31.3960 calculated for quantitative analysis.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.246-249
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• 2003

The constraints necessary guarantee using the comparison of these extrinsic parameters, which each Rotation matrix and Translation Vector must be equal to the either, except the X-axis Translation Vector. Thus, we can not yet calculate the 3D-range measurement in the end of camera calibration. To minimize this disadvantage, the Epipolar Rectification has been proposed in the literature. This paper aims to present the development of Epipolar Rectification to calibrate Stereo cameras. The required computation of the transformation mapping between points in 3D-space is based on calculating the image point that appears on new image plane by using calibrated parameters. This computation is assumed from the rotating the old ones around their optical center until focal planes becomes coplanar, thereby containing the baseline, and the Z-axis of both camera coordinate to be parallel together. The optical center positions of the new extrinsic parameters are the same as the old camera, whereas the new orientation differs from the old ones by the suitable rotations. The intrinsic parameters are the same for both cameras. So that, after completed calibration process, immediately can calculate the 3D-range measurement. And the rectification determines a transformation of each image plane such that pairs of conjugate Epipolar lines become collinear and parallel to one of the image axis. From the experimental results verify the proposed technique are agreed with the expected specifications.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.41-48
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• 2012

Using multi-sensor or multi-temporal high resolution satellite images together is essential for efficient applications in remote sensing area. The purpose of this paper is to estimate geometric difference of translations between high-resolution optical and SAR images automatically. The geometric and radiometric pre-processing steps were fulfilled to calculate the similarity between optical and SAR images by using Mutual Information method. The coarsest-level pyramid images of each sensor constructed by gaussian pyramid method were generated to estimate the initial translation difference of the x, y directions for calculation efficiency. The precise geometric difference of translations was able to be estimated by applying this method from coarsest-level pyramid image to original image in order. Yet even when considered only translation between optical and SAR images, the proposed method showed RMSE lower than 5m in all study sites.

• Journal of Broadcast Engineering
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• v.9 no.1
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• pp.64-73
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• 2004

A robust watermarking algorithm is proposed for 3D mesh models. Watermark is inserted into the 2D image which is extracted from the target 3D model. Each Pixel value of the extracted 2D image represents a distance from the predefined reference points to the face of the given 3D model. This extracted image is defined as “range image” in this paper. Watermark is embedded into the range image. Then, watermarked 3D mesh is obtained by modifying vertices using the watermarked range Image. In extraction procedure, the original model is needed. After registration between the original and the watermarked models, two range images are extracted from each 3D model. From these images. embedded watermark is extracted. Experimental results show that the proposed algorithm is robust against the attacks such as rotation, translation, uniform scaling, mesh simplification, AWGN and quantization of vertex coordinates.