• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.2
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• pp.288-293
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• 2002

It is possible to classify image data into two types according to the internal representation: one is bitmap, the other is vector. A bitmap image is represented by the two dimensional pixels whereas a vector image is represented by mathematical functions to draw vector objects such as line, rectangle and circle on the two or three dimensional space. So it is necessary for users to use a individual application program for each different image. In this paper, we present a method for design and implementation of image editing tool based on combining of bitmap and vector image.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_2
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• pp.665-672
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• 2012

Amid rapidly increasing imagery inputs and their volume in a remote sensing imagery database, Content-Based Image Retrieval (CBIR) is an effective tool to search for an image feature or image content of interest a user wants to retrieve. It seeks to capture salient features from a 'query' image, and then to locate other instances of image region having similar features elsewhere in the image database. For a CBIR approach that uses texture as a primary feature primitive, designing a texture descriptor to better represent image contents is a key to improve CBIR results. For this purpose, an extended feature vector combining the Gabor filter and co-occurrence histogram method is suggested and evaluated for quantitywise and qualitywise retrieval performance criterion. For the better CBIR performance, assessing similarity between high dimensional feature vectors is also a challenging issue. Therefore a number of distance metrics (i.e. L1 and L2 norm) is tried to measure closeness between two feature vectors, and its impact on retrieval result is analyzed. In this paper, experimental results are presented with several CBIR samples. The current results show that 1) the overall retrieval quantity and quality is improved by combining two types of feature vectors, 2) some feature is better retrieved by a specific feature vector, and 3) retrieval result quality (i.e. ranking of retrieved image tiles) is sensitive to an adopted similarity metric when the extended feature vector is employed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.298-301
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• 2008

Vector Graphics describes an image with mathematical statements instead of pixel information, Which enables easy scalability without loss in image quality and usually results in a much smaller file size compared with bitmap images. In this paper, we propose Vector Graphics Rasterizer for mobile device with scan-line edge flag algorithm. Proposed Vector Graphics Accelerator was verified with OpenVG 2D Vector image. The estimated performance of proposed Accelerator is 5 frame per second with Tiger image.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.529-535
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• 2000

In this paper, we propose a new method of designing the vector quantizer which is robustness to coding results and independent of statistical characteristics of an input image in wavelet transformed image coding processes. The most critical drawback of a conventional vector quantizer is the degradation of coding capability resulted from the discordance between quantizer objective image and statistical characteristics of training sequence which is for generating representing vector. In order to resolve the problem of conventional methods, we use independent random-variables and pseudo image to which image correlation and edge component were added, as a training sequence for generating representing vector. We have done a computer simulation in order to compare coding capability between a vector quantizer designed by the proposed method and one with the conventional method using real image as same as that is objective to coding of training sequence used in codebook generation. The results show the superiority of the proposed vector quantizer method at the aspect of coding capability compared to conventional one. They also clarify the problems of conventional methods.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.19 no.4
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• pp.44-50
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• 2011

This paper presents the algorithm for attitude determination of an aircraft using binary image. An image feature vector, which is invariant to translation, scale and rotation, is constructed to capture the functional relations between the feature vector and the corresponding aircraft attitude. An iterated least squares method is suggested for estimating the attitude of given aircraft using the constructed feature vector library. Simulation results show that the proposed algorithm yields good estimates of aircraft attitude in most viewing range, although a relatively large error occurs in some limited viewing direction.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.42-49
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• 1996

In this paper, we propose a satellite multispectral image data compression method using classified vector quantization. This method classifies each pixel vector considering band characteristics of multispectral images. For each class, we perform both intraband and interband vector quantization to romove spatial and spectral redundancy, respectively. And residual vector quantization for error images is performed to reduce error of interband vector quantization. Thus, this method improves compression efficiency because of removing both intraband(spatial) and interband (spectral) redundancy in multispectral images, effectively. Experiments on landsat TM multispectral image show that compression efficiency of proposed method is better than that of conventional method.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1987.04a
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• pp.39-41
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• 1987

In this paper we describe the syrucure of vector trellis comding system for image data coression. And the simuatlion results are compared with those of the genera VQ(vector quantlzation)on the basis of SNR search time and memory requiement

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.10
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• pp.2448-2463
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• 2013

The traditional block-based motion compensation methods in frame rate up-conversion (FRUC) only use a single uniquely motion vector field. However, there will always be some mistakes in the motion vector field whether the advanced motion estimation (ME) and motion vector analysis (MA) algorithms are performed or not. Once the motion vector field has many mistakes, the quality of the interpolated frame is severely affected. In order to solve the problem, this paper proposes a novel joint overlapped block motion compensation method (8J-OBMC) which adopts motion vectors of the interpolated block and its 8-neighbor blocks to jointly interpolate the target block. Since the smoothness of motion filed makes the motion vectors of 8-neighbor blocks around the interpolated block quite close to the true motion vector of the interpolated block, the proposed compensation algorithm has the better fault-tolerant capability than traditional ones. Besides, the annoying blocking artifacts can also be effectively suppressed by using overlapped blocks. Experimental results show that the proposed method is not only robust to motion vectors estimated wrongly, but also can to reduce blocking artifacts in comparison with existing popular compensation methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.56-65
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• 2009

Stereoscopic images consist of the left image and the right image. Thus, stereoscopic images have much amounts of data than single image. Then an efficient image compression technique is needed, the DPCM-based predicted coding compression technique is used in most video coding standards. Motion and disparity estimation are needed to realize the predicted coding compression technique. Their performing algorithm is block matching algorithm used in most video coding standards. Full search algorithm is a base algorithm of block matching algorithm which finds an optimal block to compare the base block with every other block in the search area. This algorithm presents the best efficiency for finding optimal blocks, but it has very large computational loads. In this paper, we have proposed fast disparity estimation algorithm using motion and disparity vector information of the prior frame in stereo image coding. We can realize fast disparity vector estimation in order to reduce search area by taking advantage of global disparity vector and to decrease computational loads by limiting search points using motion vectors and disparity vectors of prior frame. Experimental results show that the proposed algorithm has better performance in the simple image sequence than complex image sequence. We conclude that the fast disparity vector estimation is possible in simple image sequences by reducing computational complexities.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1889-1893
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• 2008

This paper explores the classification performance of applying to support vector machines (SVMs) for the image classification problems. In this study, we extract the color, texture and shape features of natural images and compare the performance of image classification using each individual feature and integrated features. The experiment results show that classification accuracy on the basis of color feature is better than that based on texture and shape features and the results of the integrating features also provides a better and more robust performance than individual feature. In additions, we show that the proposed classifier of SVM based approach outperforms BPNN to corporate the image classification problems.