• Journal of Biomedical Engineering Research
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• v.8 no.2
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• pp.171-176
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• 1987

Wiener filtering method was applied to the dual energy imaging procedure in digital radiography(D.R.). A linear scanning photodiode arrays with 1024 elements(0.6mm H 1.3mm pixel size) were used to obtain chest images in 0.7 sec. For high energy image acquisition, X-ray tube was set at 140KVp, 100mA with a rare-earth phosphor screen. Low energy image was obtained with X-ray tube setting at 70KVp, 150mA. These measured dual energy images are represented in the vector matrix notation as a linear discrete model including the additive random noise. Then, the object images are restored in the minimum mean square error sense using Wiener filtering method in the transformed domain. These restored high and low energy images are used for computation of the basis image decomposition. Then the basis images are linearly combined to produce bone or tissue selective images. Using this process, we could improve the signal to noise ratio characteristics in the material selective images.

• Journal of Korea Multimedia Society
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• v.11 no.5
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• pp.588-596
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• 2008

For the patients' privacy, secure access control of medical images is essentially necessary. In this paper, two types of Region of Interest (ROI)-based selective encryption schemes are proposed, which concentrate on the security of crucial parts in medical images. The first scheme randomly inverts the most significant bits of ROI coefficients in several high frequency subbands in the transform domain, which only incurs little loss on compression efficiency. The second scheme employs a symmetric key encryption to encrypt selectively the ROI data in the final code-stream, which provides sufficient confidentiality. Both of two schemes are backward compatible so as to ensure a standard bitstream compliant decoder so the encrypted images can be reconstructed without any crash.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.9-12
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• 2001

Point pattern matching schemes for finger print recognition do not guarantee robust matching performance for finger print images of poor quality. We present a finger print recognition scheme, where transformation parameter of matched ridge pairs are estimated by Hough transform and the matching hypothesis is verified by a new measure of the matching degree using selective directional information. Proposed method may exhibit extremely low FAR(False Accept Ratio) while maintaining low reject ratio even for the images of poor quality because of the robustness to the variation of minutia points.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.47-54
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• 2012

Additional high resolution satellite images, other period or site, are essential for efficient city modeling and analysis. However, the same ground objects have a radiometric inconsistency in different satellite images and it debase the quality of image processing and analysis. Moreover, in an urban area, buildings, trees, bridges, and other artificial objects cause shadow effects, which lower the performance of relative radiometric normalization. Therefore, in this study, we exclude shadow areas and suggest the selective histogram matching methods for image based application without supplementary digital elevation model or geometric informations of sun and sensor. We extract the shadow objects first using adjacency informations with the building edge buffer and spatial and spectral attributes derived from the image segmentation. And, Outlier objects like a asphalt roads are removed. Finally, selective histogram matching is performed from the shadow masked multi-temporal Quickbird-2 images.

• Journal of Information Technology Services
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• v.16 no.1
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• pp.55-72
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• 2017

Many of the studies of visual attention that are currently underway are seeking ways to make application systems that can be used in practice, and obtained good results using not only simulated images but also real-world images. However, despite that previous studies of selective visual attention are models intended to implement the human vision, few experiments verified the models with actual humans and there is no standardized data nor standardized experimental method for actual images. Therefore, in this paper, we propose a new performance evaluation techniques necessary for evaluation of visual attention systems. We developed an evaluation method for evaluating the performance of the visual attention system through comparison with the results of the human experiments on visual attention. Human experiments on visual attention is an experiments where human beings are instinctively aware of the unconscious when images are given to humans. So it can be useful for evaluating performance of the bottom-up attention system. Also we propose a new selective attention system that guides the user to effectively detect ROI regions by using spatial and temporal features adaptively selected according to the input image. We evaluated the performance of proposed visual attention system through the developed performance evaluation method, and we could confirm that the results of the visual attention system are similar to those of the human visual attention.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.29-37
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• 2021

In this paper, we propose a deep learning-based retinal vessel segmentation model for handling multi-scale information of fundus images. we integrate the selective kernel convolution into U-Net-based convolutional neural network. The proposed model extracts and segment features information with various shapes and sizes of retinal blood vessels, which is important information for diagnosing eye-related diseases from fundus images. The proposed model consists of standard convolutions and selective kernel convolutions. While the standard convolutional layer extracts information through the same size kernel size, The selective kernel convolution extracts information from branches with various kernel sizes and combines them by adaptively adjusting them through split-attention. To evaluate the performance of the proposed model, we used the DRIVE and CHASE DB1 datasets and the proposed model showed F1 score of 82.91% and 81.71% on both datasets respectively, confirming that the proposed model is effective in segmenting retinal blood vessels.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.1-8
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• 2000

Point pattern matching schemes for finger print recognition do not guarantee robust matching performance for fingerprint Images of poor quality We present a finger print recognition scheme, where transformation parameters of matched ridge pairs are estimated by Hough transform and the matching hypothesis is verified by a new measure of the matching degree using selective directional information Proposed method may exhibit extremely low FAR(False accept rate) while maintaining low reject rate even for the Images of poor quality because of the robustness to the variation of minutia points.

• Korean Institute of Interior Design Journal
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• v.24 no.6
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• pp.145-153
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• 2015

For this research with the objects of spaces in two department stores which can be referred to as representative facility of commercial space, observation test has carried out to estimate how much visitors rivet their eyes to the display of shops. In addition, to find out what effect the difference among the department types has on the selective attention to space element, the observation time was applied as a medium for estimation. The followings are the result from analyzing the observation frequency and the observation intensity feature of each section where the characteristics of design could be found at attention. First, both images of A and B had concentrative dominant-observation at left shops. In case of Image A, Customers began to observe the right shops very attentively after 25 seconds, and with Image B, the attentive observation at right and left took place alternatively after 35 seconds. In other words, regardless of the characteristics of shop displays, the left shops were observed first while in case of the observation after the early and middle time-frame the characteristics of shops were found to have effects on observation. Second, the normal observation showed some difference among attention sections over time while on the whole both images of A and B had the same highly attentive observation at the middle space. Accordingly, it could be concluded that the middle space was playing a faithful role as background for commercial spaces. Third, the ignorant observation, which is the opposite to the attentive observation, was found different between the images of A and B. When the ignorant observation is considered to have intentionality, it will be possible to set up the display which may attract the attention aggressively by the process of figuring out the characteristics of ignored shops.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.7
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• pp.629-638
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• 2000

The main difference between mono-volume rendering and multi-volume rendering is data intermixing. In this paper, we first propose a selective rendering method for fast visualizing specific volume according to the surface level and then present data intermixing method for multiple volumes. The selective rendering method is to generate distance transformed volume using a distance transform to determine the minimum distance to the nearest interesting part and then render it. The data intermixing method for multiple volumes is to combine several volumes using intensity weighted intermixing method, opacity weighted intermixing method, opacity weighted intermixing method with depth information and then render it. We show the results of selective rendering of left ventricle and right ventricle generated from EBCT cardiac images and of data intermixing for combining original volume and left ventricular volume or right ventricular volume. Our method offers a visualization technique of specific volume according to the surface level and an acceleration technique using a distance transformed volume and the effective visual output and relation of multiple images using three different intermixing methods in three-dimensional space.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.238-246
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• 2018

The production of hyper-realistic digital rendering images has been available due to radical improvements of recent digital rendering and CGI (Computer-Generated Imagery) software technologies. The photorealism of digital architectural rendering images requires further studies and discussions in that architectural visualization becomes a foundation of other fields using digital rendering technology, such as movies, games, and VR industry. The principles for achieving photorealism on digital architectural rendering images were re-defined and detailed elements were analyzed through theoretical analysis of the former studies. Four principles were drawn from the architectural rendering images produced by newly-developed technologies: physically-accurate lighting calculations, accurate object geometry representation, realistic material and texture, and characteristics of photography. The sub-elements of those four principles are categorized into either essential or selective for photorealistic imagery and the randomness of the selective elements could explain the variety of photorealistic architectural rendering styles.