• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.29-35
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• 2023

CCTV is used for various purposes such as crime prevention, public safety reinforcement, and traffic management. However, as the range and resolution of the camera improve, there is a risk of exposing personal information in the video. Therefore, there is a need for new technologies that can identify individuals while protecting personal information in images. In this paper, we propose histogram-based singular value decomposition for object identification and tracking. The proposed method distinguishes different objects present in the image using color information of the object. For object recognition, YOLO and DeepSORT are used to detect and extract people present in the image. Color values are extracted with a black-and-white histogram using location information of the detected person. Singular value decomposition is used to extract and use only meaningful information among the extracted color values. When using singular value decomposition, the accuracy of object color extraction is increased by using the average of the upper singular value in the result. Color information extracted using singular value decomposition is compared with colors present in other images, and the same person present in different images is detected. Euclidean distance is used for color information comparison, and Top-N is used for accuracy evaluation. As a result of the evaluation, when detecting the same person using a black-and-white histogram and singular value decomposition, it recorded a maximum of 100% to a minimum of 74%.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.577-578
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• 2013

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.182-185
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• 2005

Satellite cameras are calibrated before launch in detail and in general, but it cannot be guaranteed that the geometry is not changing during launch and caused by thermal influence of the sun in the orbit. Modem satellite imaging systems are based on CCD-line sensors. Because of the required high sampling rate the length of used CCD-lines is limited. For reaching a sufficient swath width, some CCD-lines are combined to a longer virtual CCD-line. The images generated by the individual CCD-lines do overlap slightly and so they can be shifted in x- and y-direction in relation to a chosen reference image just based on tie points. For the alignment and difference in scale, control points are required. The resulting virtual image has only negligible errors in areas with very large difference in height caused by the difference in the location of the projection centers. Color images can be related to the joint panchromatic scenes just based on tie points. Pan-sharpened images may show only small color shifts in very mountainous areas and for moving objects. The direct sensor orientation has to be calibrated based on control points. Discrepancies in horizontal shift can only be separated from attitude discrepancies with a good three-dimensional control point distribution. For such a calibration a program based on geometric reconstruction of the sensor orientation is required. The approximations by 3D-affine transformation or direct linear transformation (DL n cannot be used. These methods do have also disadvantages for standard sensor orientation. The image orientation by geometric reconstruction can be improved by self calibration with additional parameters for the analysis and compensation of remaining systematic effects for example caused by a not linear CCD-line. The determined sensor geometry can be used for the generation? of rational polynomial coefficients, describing the sensor geometry by relations of polynomials of the ground coordinates X, Y and Z.

• Journal of Korea Multimedia Society
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• v.16 no.10
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• pp.1135-1146
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• 2013

In this paper, we proposed a new algorithm for individual tooth region segmentation on tooth color images. The proposed algorithm used oral cavity model based on structural feature of tooth and new boundary of watershed algorithm. First, the gray scale image is obtained with emphasized tooth regions from the color images and unnecessary regions are removed on tooth images. Next, the image enhancement of tooth images is implemented using the proposed oral cavity model, and the individual tooth regions are segmented by watershed algorithm on the enhanced images. Boundary and seeds necessary to watershed algorithm are applied boundary of binary image using minimum thresholding and region maximum value. In order to evaluate performance of proposed algorithm, we conduct experiment to compare conventional algorithm with proposed algorithm. As a result of experiment, we confirmed that the proposed algorithm is more improved detection ratio than conventional algorithm at molar regions and the tooth region detection performance is improved by preventing overlap detection on oral cavity.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.483-497
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• 2018

Image mosaicking, which combines several images into one image, is effective for analyzing images and important in various fields of spatial information such as a continuous image map. The crucial processes of the image mosaicking are optimal seamline determination and color correction of mosaicked images. In this study, the overlap regions were determined by SURF (Speeded Up Robust Features) for image matching. Based on the characteristics of the edges extracted by Canny filter, seamline candidates were selected from classified edges with their characteristics, and the edges were connected by using Dijkstra algorithm. In particular, anisotropic filter and image pyramid were applied to extract reliable seamlines. In addition, it was possible to determine seamlines effectively and efficiently by utilizing building and road layers from digital maps. Finally, histogram matching and seamline feathering were performed to improve visual quality of the mosaicked images.

• Conservation Science in Museum
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• v.31
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• pp.55-70
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• 2024

Style transfer algorithms are currently undergoing active research and are used, for example, to convert ordinary images into classical painting styles. However, such algorithms have yet to produce appropriate results when applied to Korean cultural heritage images, while the number of cases for such applications also remains insufficient. Accordingly, this study attempts to develop a style transfer algorithm that can be applied to styles found among Korean cultural heritage. The algorithm was produced by improving data comprehension by enabling it to learn meaningful characteristics of the styles through representation learning and to separate the cultural heritage from the background in the target images, allowing it to extract the style-relevant areas with the desired color and texture from the style images. This study confirmed that, by doing so, a new image can be created by effectively transferring the characteristics of the style image while maintaining the form of the target image, which thereby enables the transfer of a variety of cultural heritage styles.

• Journal of the Optical Society of Korea
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• v.20 no.2
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• pp.239-244
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• 2016

Mugshot face images, routinely collected by police, usually contain both frontal and profile views. Existing automated face recognition methods exploited mugshot databases by enlarging the gallery with synthetic multi-view face images generated from the mugshot face images. This paper, instead, proposes to match the query arbitrary view face image directly to the enrolled frontal and profile face images. During matching, the 3D face shape model reconstructed from the mugshot face images is used to establish corresponding semantic parts between query and gallery face images, based on which comparison is done. The final recognition result is obtained by fusing the matching results with frontal and profile face images. Compared with previous methods, the proposed method better utilizes mugshot databases without using synthetic face images that may have artifacts. Its effectiveness has been demonstrated on the Color FERET and CMU PIE databases.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.7
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• pp.340-353
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• 2008

A computational color palette extraction model is introduced to describe paint brush objectively and efficiently. In this model, a color palette is defined as a minimum set of colors in which a painting can be displayed within error allowance and extracted by the two step processing of color grouping and major color extraction. The color grouping controls the resolution of colors adaptively and produces a basic color set of given painting images. The final palette is obtained from the basic color set by applying weighted k-means clustering algorithm. The extracted palettes from several famous painters are displayed in a 3-D color space to show the distinctive palette styles using RGB and CIE LAB color models individually. And the two experiments of painter classification and color transform of photographic image has been done to check the performance of the proposed method. The results shows the possibility that the proposed palette model can be a computational color analysis metric to describe the paint brush, and can be a color transform tool for computer graphics.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.73-80
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• 2005

Recently there have been many efforts to support searching and browsing based on the visual content of image and multimedia data. Most existing approaches to content-based image retrieval rely on query by example or user based low-level features such as color, shape, texture. But these methods of query are not easy to use and restrict. In this paper we propose a method for automatic color object extraction and labelling to support multiple queries of content-based image retrieval system. These approaches simplify the regions within images using single colorizing algorithm and extract color object using proposed Color and Spatial based Binary tree map(CSB tree map). And by searching over a large of number of processed regions, a index for the database is created by using proposed labelling method. This allows very fast indexing of the image by color contents of the images and spatial attributes. Futhermore, information about the labelled regions, such as the color set, size, and location, enables variable multiple queries that combine both color content and spatial relationships of regions. We proved our proposed system to be high performance through experiment comparable with another algorithm using 'Washington' image database.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.10
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• pp.920-927
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• 2013

Chroma key technique which composes images by separating an object from its background in specific color has restrictions on color and space. Especially, unlike general chroma key technique, image composition for stereo 3D display requires natural image composition method in 3D space. The thesis attempted to compose images in 3D space using depth keying method which uses high resolution depth information. High resolution depth map was obtained through camera calibration between the DSLR and Kinect sensor. 3D mesh model was created by the high resolution depth information and mapped with RGB color value. Object was converted into point cloud type in 3D space after separating it from its background according to depth information. The image in which 3D virtual background and object are composed obtained and played stereo 3D images using a virtual camera.