• Journal of Platform Technology
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• v.10 no.3
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• pp.44-50
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• 2022

Research on facial age estimation is being actively conducted because it is used in various application fields. Facial images taken in various environments often have occlusions, and there is a problem in that performance of age estimation is degraded. Therefore, we propose age estimation method by creating an occluded part using image extrapolation technology to improve the age estimation performance of an occluded face image. In order to confirm the effect of occlusion in the image on the age estimation performance, an image with occlusion is generated using a mask image. The occluded part of facial image is restored using SpiralNet, which is one of the image extrapolation techniques, and it is a method to create an occluded part while crossing the edge of an image. Experimental results show that age estimation performance of occluded facial image is significantly degraded. It was confirmed that the age estimation performance is improved when using a face image with reconstructed occlusions using SpiralNet by experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2385-2388
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• 2005

In this paper, we propose the estimation method for the image affine information for computer vision. The first estimation method is given based on the XYS image normalization and the second estimation method is based on the image normalization by Pei and Lin. The XYS normalization method turns out to have better performance than the method by Pei and Lin. In addition, we show that rotation and aspect ratio information can be obtained using the central moments of both the original image and the sensed image. Finally, we propose the modified version of the normalization method so that we may control the size of the image.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.18-24
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• 2008

In this paper we propose a novel method which improves digital image stabilization performance using adoptive selection of motion estimation area. Candidate area for motion estimation is decided and through two processes, multi image reference and edge energy distinction, final motion estimation area is selected. Then Motion estimation and compensation is following in selected area. Experimental results show that proposed method improves performance of digital image stabilization.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.1058-1070
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• 2014

There are two major ways to implement depth estimation, multiple image depth estimation and single image depth estimation, respectively. The former has a high hardware cost because it uses multiple cameras but it has a simple software algorithm. Conversely, the latter has a low hardware cost but the software algorithm is complex. One of the recent trends in this field is to make a system compact, or even portable, and to simplify the optical elements to be attached to the conventional camera. In this paper, we present an implementation of depth estimation with a single image using a graphics processing unit (GPU) in a desktop PC, and achieve real-time application via our evolutional algorithm and parallel processing technique, employing a compute shader. The methods greatly accelerate the compute-intensive implementation of depth estimation with a single view image from 0.003 frames per second (fps) (implemented in MATLAB) to 53 fps, which is almost twice the real-time standard of 30 fps. In the previous literature, to the best of our knowledge, no paper discusses the optimization of depth estimation using a single image, and the frame rate of our final result is better than that of previous studies using multiple images, whose frame rate is about 20fps.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.33 no.1
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• pp.68-75
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• 1997

In this paper, we propose the improved initial image estimation method for a fast fractal image decoding. When the correlation between a domain and a range is given as the linear equation, the value of initial image estimation using the conventional method is the intersection between its linear equation and y=x. If the gradient of linear equation is large, that the difference of the value between each adjacent pixels is large, the conventional method has disadvantage which has the impossibility of exact estimation. The method of the proposed initial image estimation performs well by two steps. he first step can improve the disadvantage of the conventional method. The second step upgrades the range value which was found previous step by referring information of its domain. Though the computational complexity for the initial image estimation increses slightly, the total computational complexity decreases by 30% than that of the conventional method because of diminishing in the number of iterations.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.118-126
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• 2020

In this paper, we present an effective single image fog removal by using the Joint Bright and Dark Channel (JBDC) and pixel-based transmission estimation to enhance the visibility of outdoor images susceptible to degradation due to weather and environmental conditions. The conventional methods include refinement process of coarse transmission with heavy computational complexity. The proposed transmission estimation reveals excellent edge-preserving performance and does not require the refinement process. We estimate the atmospheric light in pixel-based fashion, which can improve the transmission estimation performance and visual quality of the restored image. Moreover, we propose an adaptive transmission estimation to enhance the visual quality specifically in sky regions. Comprehensive experiments on various fog images show that the proposed method exhibits reduced computational complexity and excellent fog removal performance, compared with the existing methods; thus, it can be applied to various fields including real-time devices.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.6
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• pp.339-344
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• 2013

This paper presents an automatic focal length estimation method to correct the fisheye lens distortion in a spatially adaptive manner. The proposed method estimates the focal length of the fisheye lens by generating two reference focal lengths. The distorted fisheye lens image is finally corrected using the orthographic projection model. The experimental results showed that the proposed focal length estimation method is more accurate than existing methods in terms of the loss rate.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.2
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• pp.146-156
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• 1998

Thispapr proposes hybrid navigation parameter estimation using sequential aerial images. The proposed navigation parameter estimation system is composed of two parts: relative position estimation and absolute position estimation. the relative position estimation recursively computes the current velocity and absolute position estimation. The relative position estimation recursively computes the current velocity and position of an aircraft by accumulating navigation parameters extracted from two succesive aerial images. Simple accumulation of parameter values decreases reliability of the extracted parameters as an aircraft goes on navigating. therefore absolute position estimation is required to compensate for position error generated in the relative position step. The absolute position estimation algorithm combining image matching and digital elevation model(DEM) matching is presented. Computer simulation with real aerial image sequences shows the efficiency of the proposed hybrial algorithm.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1745-1753
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• 2004

A method of estimating the pose of a three-dimensional object from a set of two-dimensioal images based on parametric eigenspace method is proposed. A Gaussian blurred edge image is used as an input image instead of the original image itself as has been used previously. The set of input images is compressed using K-L transformation. By comparing the estimation errors for the original, blurred original, edge, and blurred edge images, we show that blurring with the Gaussian function and the use of edge images enhance the data compression ratio and decrease the resulting from smoothing the trajectory in the parametric eigenspace, thereby allowing better pose estimation to be achieved than that obtainable using the original images as it is. The proposed method is shown to have improved efficiency, especially in cases with occlusion, position shift, and illumination variation. The results of the pose angle estimation show that the blurred edge image has the mean absolute errors of the pose angle in the measure of 4.09 degrees less for occlusion and 3.827 degrees less for position shift than that of the original image.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.621-624
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• 1999

This paper describes a distance estimation method of object's motion in soccer image sequence by tracking field features. And we quantitatively evaluate the estimation accuracy We suppose that the input image sequence is taken with a camera on static axis and includes only zooming and panning transformation between frames. Adaptive template matching is adopted for non-rigid object tracking. For background compensation, feature templates selected from reference frame image are matched in following frames and the matched feature point pairs are used in computing Affine motion parameters. A perspective displacement field model is used for estimating the real distance between two position on Input Image. To quantitatively evaluate the accuracy of the estimation, we synthesized a 3 dimensional virtual stadium with graphic tools and experimented on the synthesized 2 dimensional image sequences. The experiment shows that the average of the error between the actual moving distance and the estimated distance is 1.84%.