• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.2
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• pp.111-116
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• 2008

The study installed non metric camera which was a 10 Mega Pixel camera in RC Helicopter. And the study controlled images hotographed in air on land, considering their overlap. The study could express DEM by abstracting TIN from the acquired images through image registration. Also, the study compared and examined accuracy between reference point and check point observed by Total Station which was a conventional type of survey. As the results, the study could get errors of $-0.194{\sim}0.224\;m$ on X axis, $-0.088{\sim}0.180\;m$ on Y axis and $-0.286{\sim}0.285\;m$ on Z axis. Expressing an error's RMSE in the checkpoint, the study could get of 0.021388 m on X axis, 0.015285 m on Y axis and 0.041872 m on Z axis. It is judged that the above photographing and analyzing technique are better than the existing Total Station to acquire more terrain elevation data.

• The Korean Journal of Applied Statistics
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• v.21 no.2
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• pp.233-245
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• 2008

In this work, a new adaptive weighted mean filter is proposed for preserving image details while effectively suppressing impulse noise. The proposed filter is based on a noise pixel detection-estimation strategy. All the pixels are first detected using an impulse noise detector. Then the detected noise pixels are replaced with the output of the weighted mean filter over adaptive working window according to the rate of corrupted neighborhood pixels, while noise-free pixels are left unaltered. We compare the proposed filter to other existing filters in the qualitative measure and quantitative measures such as PSNR and MAE as well as computation time to verify the capability of the proposed filter. Extensive simulations show that the proposed filter performs better than other filters in impulse noise suppression and detail preservation without increasing of running time.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.3_4
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• pp.205-212
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• 2003

In this paper, we propose a simple and efficient hardware-supported antialiasing algorithm and its rendering scheme. The proposed method can efficiently reduce the required memory bandwidth as well as memory size compared to a conventional supersampling when rendering 3D models. In addition, it can provide almost the same high quality scenes as supersampling does. In this paper, we have introduced the RUF (Recently Used Fragment) buffer that stores some or whole parts of a fragment or two more the merged results of fragments that recently used in color calculation. We have also proposed a color calculation algorithm to deteriorate the image quality as referencing the RUF buffer. Because of the efficiency presented in the proposed algorithm, the more number of sampling points increases the more memory saving ratio we can gain relative to the conventional supersampling. In our simulation, the proposed method can reduce the amount of memory size by 31% and the memory bandwidth by 11% with a moderate pixel color difference of 1.3% compared to supersampling for 8 sparse sampling points.

• Journal of Korea Multimedia Society
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• v.5 no.3
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• pp.255-262
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• 2002

A boundary sequence can be a good representation of arbitrary shapes, because it can represent them simply and precisely. However, boundary sequences have not been used as a representation of arbitrary shapes, because the pixel-based shape-features such as area, centroid, orientation, projection and so forth, could not be computed directly from them. In this paper, we show that the shape-features can be easily computed from the boundary sequences by introducing the cross-sections that are defined as vertical (or horizontal) line segments in a shape. A cross-section generation method is proposed, which generates cross-sections of the shape efficiently by tracing the boundary sequence of the shape once. Furthermore, a boundary sequence extraction method is also proposed, which generates a boundary sequence for each shape in a binary image automatically The proposed methods work well even if a shape has holes. Eventually, we show that a boundary sequence can be used effectively for representing arbitrary shapes.

• Journal of Korea Multimedia Society
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• v.15 no.5
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• pp.639-650
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• 2012

In 2009, Tsai et al. proposed reversible image hiding scheme using linear prediction coding and histogram shifting. Tsai et al.'s scheme improved the hiding capacity of Ni et al.'s scheme by using the prediction coding and two histograms. However, Tsai et al.'s scheme has problems. In the prediction coding, the basic pixel is not used from embedding procedure. Many additional communication data are generated because two peak and zero point pairs are generated by each block. To solve the problems, this paper proposes a novel reversible data hiding scheme based on modulo operation and histogram shifting. In experimental results, the hiding capacity was increased by 28% than Tsai et al.'s scheme. However, the additional communication data was decreased by 71%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.58-64
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• 2016

In this paper presents Robust k-means clustering-based high-speed bar code decoding method to blur and lighting. for fast operation speed and robust decoding to blur, proposed method uses adaptive local threshold binarization methods that calculate threshold value by dividing blur region and a non-blurred region. Also, in order to prevent decoding fail from the noise, decoder based on k-means clustering algorithm is implemented using area data summed pixel width line of the same number of element. Results of simulation using samples taken at various worst case environment, the average success rate of proposed method is 98.47%. it showed the highest decoding success rate among the three comparison programs.

• Journal of Navigation and Port Research
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• v.32 no.5
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• pp.355-361
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• 2008

Stereo matching is one of the most active research areas in computer vision. In this paper, we propose a stereo matching scheme using genetic algorithm for object depth recognition. The proposed approach considers the matching environment as an optimization problem and finds the optimal solution by using an evolutionary strategy. Accordingly, genetic operators are adapted for the circumstances of stereo matching. An individual is a disparity set. Horizontal pixel line of image is considered as a chromosome. A cost function is composed of certain constraints which are commonly used in stereo matching. Since the cost function consists of intensity, similarity and disparity smoothness, the matching process is considered at the same time in each generation. The LoG(Laplacian of Gaussian) edge is extracted and used in the determination of the chromosome. We validate our approach with experimental results on stereo images.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.117-140
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• 2013

Hindi is the most widely spoken language in India, with more than 300 million speakers. As there is no separation between the characters of texts written in Hindi as there is in English, the Optical Character Recognition (OCR) systems developed for the Hindi language carry a very poor recognition rate. In this paper we propose an OCR for printed Hindi text in Devanagari script, using Artificial Neural Network (ANN), which improves its efficiency. One of the major reasons for the poor recognition rate is error in character segmentation. The presence of touching characters in the scanned documents further complicates the segmentation process, creating a major problem when designing an effective character segmentation technique. Preprocessing, character segmentation, feature extraction, and finally, classification and recognition are the major steps which are followed by a general OCR. The preprocessing tasks considered in the paper are conversion of gray scaled images to binary images, image rectification, and segmentation of the document's textual contents into paragraphs, lines, words, and then at the level of basic symbols. The basic symbols, obtained as the fundamental unit from the segmentation process, are recognized by the neural classifier. In this work, three feature extraction techniques-: histogram of projection based on mean distance, histogram of projection based on pixel value, and vertical zero crossing, have been used to improve the rate of recognition. These feature extraction techniques are powerful enough to extract features of even distorted characters/symbols. For development of the neural classifier, a back-propagation neural network with two hidden layers is used. The classifier is trained and tested for printed Hindi texts. A performance of approximately 90% correct recognition rate is achieved.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.1
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• pp.13-22
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• 2000

We present a method that enhances the rendering speed of z-buffer algorithm using temporal coherence between two contiguous frames on fixed viewing conditions. Conventional z-buffer algorithm stores depth value for each pixel on a view plane while rendering some polygons, then it determines the visibility of the remaining polygons based on the stored depth values. If we can get color and depth information for some polygons without rendering, it is possible to generate an image by rendering only the remaining ones. In case of high frame rate, we can find the fact that sets of static polygons of the two contiguous frames are almost the same. This temporal coherence enables us to get the color and depth information of static polygons efficiently. Our algorithm stores color and depth information of static polygons and reuses it for generating the next frame. This method can be easily implemented since it does not require complex data structure and modification for conventional z-buffer algorithm. Also it is adequate for hardware implementation.

• Journal of Broadcast Engineering
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• v.14 no.4
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• pp.409-418
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• 2009

This paper proposes a method to estimate the flow speed of pedestrians in surveillance videos. In the proposed method, the average moving speed of pedestrians is measured by estimating the size of real-world motion from the observed motion vectors. For this purpose, a pixel-to-meter conversion factor is introduced which is calculated from camera parameters. Also, the height information, which is missing because of camera projection, is predicted statistically from simulation experiments. Compared to the previous works for flow speed estimation, our method can be applied to various camera views because it separates scene parameters explicitly. Experiments are performed on both simulation image sequences and real video. In the experiments on simulation videos, the proposed method estimated the flow speed with average error of about 0.08m/s. The proposed method also showed promising results for the real video.