• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1033-1039
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• 2012

In this paper, a simple and robust algorithm is proposed for detecting each steel plate from a image which contains several steel plates. Steel plate is characterized by line edge, so line detection is a fundamental task for analyzing and understanding of steel plate images. To detect the line edge, the proposed algorithm uses the small eigenvalue analysis. The proposed approach scans an input edge image from the top left corner to the bottom right corner with a moving mask. A covariance matrix of a set of edge pixels over a connected region within the mask is determined and then the statistical and geometrical properties of the small eigenvalue of the matrix are explored for the purpose of straight line detection. Using the detected line edges, each plate is determined based on the directional information and the distance information of the line edges. The results of the experiments emphasize that the proposed algorithm detects each steel plate from a image effectively.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.19-25
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• 2013

Recently, the high-resolution satellite images is used the land cover and status data for the natural resources or environment management very helpful. The SVM algorithm of image processing has been used in various field. However, classification accuracy by SVM algorithm can be changed by various kernel functions and parameters. In this paper, the typical kernel function of the SVM algorithm was applied to the KOMPSAT-2 image and than the result of land cover performed the accuracy analysis using the checkpoint. Also, we carried out the analysis for selected the SVM kernel function from the land cover of the target region. As a result, the polynomial kernel function is demonstrated about the highest overall accuracy of classification. And that we know that the polynomial kernel and RBF kernel function is the best kernel function about each classification category accuracy.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.34-40
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• 2003

The paper presents a method to detect dissolve shots of video scene change detections in an MPEG compressed domain. The proposed algorithm uses color-R DCT coefficients of Ⅰ, P-frames for a fast operation and accurate detection and a minimum decoding process in MPEG sequences. The paper presents a method to detect dissolve shot for three-dimensional visualization and analysis of Image in order to recognize easily in computer as a human detects accurately shots of scene change. First, Color-R DCT coefficients for 8*8 units are obtained and the features are summed in a row. Second, Four-step analysis are Performed for differences of the sum in the frame sequences. The experimental results showed that the algorithm has better detection performance, such as precision and recall rate, than the existing method using an average for all DC image by performing four step analysis. The algorithm has the advantage of speed, simplicity and accuracy. In addition. it requires less amount of storage.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3454-3459
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• 2013

Sumi-e is one of the art work that uses not only ink line but also color painting. This technique is well known as a representative Asian painting style and widely used in movie, advertisement poster and various effect in camera device. In this paper, we propose an algorithm that can generate result image with Sumi-e effects of example image based on computer graphics and image processing techniques. For this, we pass two steps. The first is painting expression step. We used texture transfer technique to generate result with texture effect of reference image by analyzing numerically. The second step is ink-painting effect generation step. We express ink-painting effect in outline by considering intensity variation in edge of example image. Our algorithm can express various Sumi-e style based on selected reference image. So it can be utilized to various contents generating research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6069-6091
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• 2017

Augmented Reality (AR) overlays virtual information on real world data, such as displaying useful information on videos/images of a scene. This paper presents an Enhanced AR (EAR) system that displays useful statistical players' information on captured images of a sports game. We focus on the situation where the input image is degraded by strong sunlight. Proposed EAR system consists of an image enhancement technique to improve the accuracy of subsequent player and face detection. The image enhancement is followed by player and face detection, face recognition, and players' statistics display. First, an algorithm based on multi-scale retinex is proposed for image enhancement. Then, to detect players' and faces', we use adaptive boosting and Haar features for feature extraction and classification. The player face recognition algorithm uses boosted linear discriminant analysis to select features and nearest neighbor classifier for classification. The system can be adjusted to work in different types of sports where the input is an image and the desired output is display of information nearby the recognized players. Simulations are carried out on 2096 different images that contain players in diverse conditions. Proposed EAR system demonstrates the great potential of computer vision based approaches to develop AR applications.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.911-921
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• 2004

Accurate minutiae extraction from input fingerprint images is one of the critical modules in robust automatic fingerprint identification system. However, the performance of a minutiae extraction is heavily dependent on the quality of the input fingerprint images. If the preprocessing is performed according to the fingerprint image characteristics in the image enhancement step, the system performance will be more robust. In this paper, we propose a knowledge-based preprocessing method, which extracts S features (the mean and variance of gray values, block directional difference, orientation change level, and ridge-valley thickness ratio) from the fingerprint images and analyzes image quality with Ward's clustering algorithm, and enhances the images with respect to oily/neutral/dry characteristics. Experimental results using NIST DB 4 and Inha University DB show that clustering algorithm distinguishes the image Quality characteristics well. In addition, the performance of the proposed method is assessed using quality index and block directional difference. The results indicate that the proposed method improves both the quality index and block directional difference.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.20-25
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• 2019

Most multimedia signals contain image data, so the problem of efficient processing and transmitting the image data is an important task of the information society. This paper proposes a compression algorithm that reduces the color bits according to importance using YUV color space among the various methods of compressing image data. 4: 2: 2 subsampling is the standard in the field of video. Using the color information and the characteristics of the human retina, YUV color data was reduced by 4: 2: 2 subsampling. The YUV images and RGB images can be interconverted using the transformation matrix. The image data was converted into color space by YUV, and the relatively low U and V bits were subjected to a downscaling operation. The data was then compressed through 4: 2: 2 subsampling. The performance of the proposed algorithm was compared and analyzed by a comparison with existing methods. As a result of the analysis, it was possible to compress the image without reducing the information of the low importance color element and without significant deterioration in the quality compared to the original.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.1
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• pp.191-197
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• 2013

Conventional CT and MRI scans produce cross-section slices of body that are viewed sequentially by radiologists who must imagine or extrapolate from these views what the 3 dimensional anatomy should be. By using sophisticated algorithm and high performance computing, these cross-sections may be rendered as direct 3D representations of human anatomy. The 2D medical image analysis forced to use time-consuming, subjective, error-prone manual techniques, such as slice tracing and region painting, for extracting regions of interest. To overcome the drawbacks of 2D medical image analysis, combining with medical image processing, 3D visualization is essential for extracting anatomical structures and making measurements. We used the gray-level thresholding, region growing, contour following, deformable model to segment human organ and used the feature vectors from texture analysis to detect harmful cancer. We used the perspective projection and marching cube algorithm to render the surface from volumetric MR and CT image data. The 3D visualization of human anatomy and segmented human organ provides valuable benefits for radiation treatment planning, surgical planning, surgery simulation, image guided surgery and interventional imaging applications.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.10
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• pp.38-45
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• 2004

In this paper, a parallel visualization algorithm is proposed for efficient visualization of the massive data generated from large-scale parallel finite element analysis through investigating the characteristics of parallel rendering methods. The proposed parallel visualization algorithm is designed to be highly compatible with the characteristics of domain-wise computation in parallel finite element analysis by using the sort-last-sparse approach. In the proposed algorithm, the binary tree communication pattern is utilized to reduce the network communication time in image composition routine. Several benchmarking tests are carried out by using the developed in-house software, and the performance of the proposed algorithm is investigated.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.285-290
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• 2009

In this paper, we propose a new algorithm that improves the lossless data compression rate. The proposed algorithm lessens the redundancy and improves the compression rate evolutionarily around 40 up to 80 percentile depending on the characteristics of binary images used for compression. In order to demonstrate the superiority of the proposed method, the comparison between the proposed method and the LZ78 (LZ77) is demonstrated through experimental results theoretical analysis.