• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.60-65
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• 2016

This paper introduces the non-local means (NLM) algorithm for image denoising, and also introduces an improved algorithm which is based on the principal component analysis (PCA). To do the PCA, a covariance matrix of a given image should be evaluated first. If we let the size of neighborhood patches of the NLM S × S², and let the number of pixels Q, a matrix multiplication of the size S² × Q is required to compute a covariance matrix. According to the characteristic of images, such computation is inefficient. Therefore, this paper proposes an efficient method to compute the covariance matrix by sampling the pixels. After sampling, the covariance matrix can be computed with matrices of the size S² × floor (Width/l) × (Height/l).

• Journal of Advanced Navigation Technology
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• v.18 no.2
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• pp.151-157
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• 2014

Recently UAV(unmanned aerial vehicle) is frequently used not only for military purpose but also for civil purpose. UAV automatically navigates following the coordinates input in advance using GPS information. However it is impossible when GPS cannot be received because of jamming or external interference. In order to solve this problem, we propose a real-time segmentation and classification algorithm for the specific regions from UAV image in this paper. We use the super-pixels algorithm using graph-based image segmentation as a pre-processing stage for the feature extraction. We choose the most ideal model by analyzing various color models and mixture color models. Also, we use support vector machine for classification, which is one of the machine learning algorithms and can use small quantity of training data. 18 color and texture feature vectors are extracted from the UAV image, then 3 classes of regions; river, vinyl house, rice filed are classified in real-time through training and prediction processes.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.10
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• pp.777-788
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• 2006

This paper describes a displacement mapping technique which represents protruded shapes on the surface of an object. Previous approaches for image-based displacement mapping can represent only shapes depressed from the polygon surface. The proposed technique can represent shapes protruded from the underlying surface in real-time. Two auxiliary surfaces which are perpendicular to the underlying surface are added along the boundary of the polygon surface, in order to represent the pixels which overflow over the boundary of the polygon surface. The proposed approach can represent accurate silhouette of protruded shape. It can represent not only smooth displacement of protruded shape, but also abrupt displacement such as perpendicular protrusion by means of adding the supplementary texture information to the steep surface of protruded shape. By per-pixel instructions on the programmable GPU this approach can be executed in real-time. It provides an effective solution for the representation of protruded shape such as high-rise buildings on the ground.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1C
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• pp.92-101
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• 2004

This paper proposes a algorithm to extract the variety region (object) from video for the real-time encoding of MPEG-4 based. The previous object segmentation methods cannot used the videophone or videoconference required by real-time processing. It is difficult to transfer a video to real-time because it increased complexity for the operation of each pixel on the spatial segmentation and temporal segmentation method proposed by MPEG-4 Working Group. But algorithm proposed for this thesis not operates a pixel unit but operates a macro block unit. Thus this enables real-time transfer. But this algorithm cannot extract several object for a image using proposed algorithm as previous algorithm. On system constructed by encoder and decoder. A proposed algorithm inserted for encoder as pre-process.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.4
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• pp.232-239
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• 2003

This paper discusses the design and implementation of a human-oriented interface based on computer vision that efficiently controls presentation slides. The user does not have to be confined to a keyboard or mouse any more, and can move around more freely because slides for presentation can be up and down using a general laser pointer that is used for presentation. Regions for virtual buttons are set on the slide so that the user can conveniently point the buttons using the laser pointer. We have proposed a simple and efficient method that computes the button areas in the image without complicated calibration. The proposed method has been implemented based on Microsoft PowerPoint ; moreover it can be applied to other PowerPoint-like presentation softwares. Our method for human-centered slide control enables the user to give audiences a more interactive presentation in a natural way.

• Journal of Korea Multimedia Society
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• v.15 no.8
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• pp.977-985
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• 2012

The purpose of this study was to present a non-photorealistic rendering technique that is efficient in single images and moving images. In case of single images, they could be processed in a real-time base by realizing flow-based DoG filter and bilateral filter, which have been frequently used in the single image NPR technique recently, in the CUDA environment. In case of moving images, the investigator presented not the existing method of NPR moving images which generating images by applying the single image NPR technique to every frame, but the method of using the single image NPR technique in the first frame and stylizing it, and then of using the motion vector-based pixel mapping in the second frame on and copying the bright values of pixels that move on the frame into the location of next frame's motion vector, thus reducing unnecessary volume of calculation and maintaining the consistency between frames. In this study, the performance of this method was proved via an experiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.371-379
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• 2009

In this paper, we proposed new de-interlacing algorithm for video data using intensity gradient filter and median filter with texture detection in the image block. We first introduce the texture detection. According to texture detection, the current region is determined into smooth region or texture region. In case that the smooth region interpolated by median filter. In addition, in case of the texture region, we calculate missing pixel value using intensity gradient filter. Therefore, we analyze the local region feature using the texture detection and classify each missing pixel into two categories. And then, based on the classification result, a different de-interlacing algorithm is activated in order to obtain the best performance. Experimental results show that the proposed algorithm performs well with a variety of moving sequences compared with conventional intra-field method in the literature.

• Ecology and Resilient Infrastructure
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• v.6 no.4
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• pp.258-266
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• 2019

This study was conducted to apply natural river technologies to levees and examine the results. The new eco-friendly bio-polymer was applied, a combination of eco-friendly biopolymers and soil, to levee slope to enhance durability and eco-friendliness and to establish reinforcement measures against unstable levees due to overtopping. A semi-prototype levee of 1 m in height, 3 m in width, with a 1:2 slope and 5 m length, was constructed at the Andong River Experiment Center. The bio-soil mixed with the biopolymer and the soil at an appropriate ratio was treated with a 5 cm thickness on the surface of levee to perform the stability evaluation according to overtopping. Using the pixel-based analysis technique using the image analysis program, the breached area of levee slope was calculated over time. As a result, the time for complete decay occurs more than 12 times than that of ordinary soil levee. Therefore, when the new substance is applied to the surface of levee, the decay delay effect appears to be high.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.504-511
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• 2014

This paper presents a hybrid recognition method, which is based on the nonlinear histogram equalization and the multidimensional intensity variation of an images. The nonlinear histogram equalization based on a adaptively modified function is applied to improve the quality by adjusting the brightness of the image. The multidimensional intensity variation by considering the a extent of 4-step changes in brightness between the adjacent pixels is also applied to reflect accurately the attributes of image. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to comprehensively measure the similarity between the images. The NCC is considered by the intensity variation of each 2-direction(x-axis and y-axis) image. The proposed method has been applied to the problem for recognizing the 50-face images of 40*40 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the histogram equalization, or the linear histogram equalization, respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.33-45
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• 2011

In this paper, we present a method for extracting video objects efficiently by using the modified graph cut algorithm based on contour information. First, we extract objects at the first frame by an automatic object extraction algorithm or the user interaction. To estimate the objects' contours at the current frame, motion information of objects' contour in the previous frame is analyzed. Block-based histogram back-projection is conducted along the estimated contour point. Each color model of objects and background can be generated from back-projection images. The probabilities of links between neighboring pixels are decided by the logarithmic based distance transform map obtained from the estimated contour image. Energy of the graph is defined by predefined color models and logarithmic distance transform map. Finally, the object is extracted by minimizing the energy. Experimental results of various test images show that our algorithm works more accurately than other methods.