• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.376-379
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• 2008

This paper presents an image retrieval algorithm based on feature vector using color of histogram refinement for a faster and more efficient search in the process of content based image retrieval. First, we segment each of R, G, and B images from RGB color image and extract their respective histograms. Secondly, these histograms of individual R, G and B are divided into sixteen of bins each. Finally, we extract the maximum pixel values in each bins' histogram, which are calculated, compared and analyzed, Now, we can perform image retrieval technique using these maximum pixel value. Hence, the proposed algorithm of this paper effectively extracts features by comparing input and database images, making features from R, G and B into a feature vector table, and prove a batter searching performance than the current algorithm that uses histogram matching and ranks, only.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.469-486
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• 2018

We propose an enhanced version of the local binary pattern (LBP) operator for texture extraction in images in the context of image retrieval. The novelty of our proposal is based on the observation that the LBP exploits only the lowest kind of local information through the global histogram. However, such global Histograms reflect only the statistical distribution of the various LBP codes in the image. The block based LBP, which uses local histograms of the LBP, was one of few tentative to catch higher level textural information. We believe that important local and useful information in between the two levels is just ignored by the two schemas. The newly developed method: gradual locality integration of binary patterns (GLIBP) is a novel attempt to catch as much local information as possible, in a gradual fashion. Indeed, GLIBP aggregates the texture features present in grayscale images extracted by LBP through a complex structure. The used framework is comprised of a multitude of ellipse-shaped regions that are arranged in circular-concentric forms of increasing size. The framework of ellipses is in fact derived from a simple parameterized generator. In addition, the elliptic forms allow targeting texture directionality, which is a very useful property in texture characterization. In addition, the general framework of ellipses allows for taking into account the spatial information (specifically rotation). The effectiveness of GLIBP was investigated on the Corel-1K (Wang) dataset. It was also compared to published works including the very effective DLEP. Results show significant higher or comparable performance of GLIBP with regard to the other methods, which qualifies it as a good tool for scene images retrieval.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3670-3676
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• 2011

A cell animation is represented by one background cell, and there is much difference of images when its shot is changed. Also, it does not have a lot of colors since people themselves draw it. In order to effectively detect shot transitions of cell animations while fully considering their intrinsic characteristics, in this paper, we propose a animation shot boundary detection algorithm that utilizes color and block-based histograms step by step. The suggested algorithm first converts RGB color space into HSI color one, and coarsely decides if adjacent frames contains a shot transition by performing color difference operation between two images. If they are considered to have a shot transition candidate, we calculate color histograms for 9 sub-regions of the adjacent images and apply weights to them. Finally, we determine whether there is a real shot transition by analyzing the weighted sum of histogram values. In experiments, we show that our method is superior to others.

• Science of Emotion and Sensibility
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• v.16 no.2
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• pp.187-194
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• 2013

The final aim of the present study is to build a system of converting a color image into musical elements based on a synesthetic perception, emulating human synesthetic skills, which make it possible to associate a color image with a specific sound. This can be done on the basis of the similarities between physical frequency information of both light and sound. As a first step, an input true color image is converted into hue, saturation, and intensity domains based on a color model conversion theory. In the next step, musical elements including note, octave, loudness, and duration are extracted from each domain of the HSI color model. A fundamental frequency (F0) is then extracted from both hue and intensity histograms. The loudness and duration are extracted from both intensity and saturation histograms, respectively. In experiments, the proposed system on the conversion of a color image into musical elements was implemented using standard C and Microsoft Visual C++(ver. 6.0). Through the proposed system, the extracted musical elements were synthesized to finally generate a sound source in a WAV file format. The simulation results revealed that the musical elements, which were extracted from an input RGB color image, reflected in its output sound signals.

• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.515-524
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• 2013

In this paper, we propose a novel face authentication method based on LBP matching of individual major blocks in mobile environment. In order to construct individual major blocks from photos, we find the blocks that have the highest similarity and use different numbers of blocks depending on the probability distribution by applying threshold. And, we use multi-radius LBP histograms in the determination of individual major blocks to improve performance of generic LBP histogram based approach. By using the multi-radius LBP histograms in face authentication, we can successfully reduce the false acceptance rate compare to the previous methods. Also, we can see that the proposed method shows low error rate about 7.72% compare to the pervious method in spite of use small number of blocks about 44.59% only.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.17
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• pp.7371-7375
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• 2014

Background: Concurrent chemo-radiotherapy is the recommended standard treatment modality for patients with locally advanced lung cancer. The purpose of three-dimensional conformal radiotherapy (3DCRT) is to minimize normal tissue damage while a high dose can be delivered to the tumor. The most common dose limiting side effect of thoracic RT is radiation pneumonia (RP). In this study we evaluated the relationship between dose-volume histogram parameters and radiation pneumonitis. This study targeted prediction of the possible development of RP and evaluation of the relationship between dose-volume histogram (DVH) parameters and RP in patients undergoing 3DCRT. Materials and Methods: DVHs of 41 lung cancer patients treated with 3DCRT were evaluated with respect to the development of grade ${\geq}2$ RP by excluding gross tumor volume (GTV) and planned target volume (PTV) from total (TL) and ipsilateral (IPSI) lung volume. Results: Were admitted statistically significant for p<0.05. Conclusions: The cut-off values for V5, V13, V20, V30, V45 and the mean dose of TL-GTV; and V13, V20,V30 and the mean dose of TL-PTV were statistically significant for the development of Grade ${\geq}2$ RP. No statistically significant results related to the development of Grade ${\geq}2$ RP were observed for the ipsilateral lung and the evaluation of PTV volume. A controlled and careful evaluation of the dose-volume histograms is important to assess Grade ${\geq}2$ RP development of the lung cancer patients treated with concurrent chemo-radiotherapy. In the light of the obtained data it can be said that RP development may be avoided by the proper analysis of the dose volume histograms and the application of optimal treatment plans.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.73-81
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• 2011

In this paper, an improved block-based background modeling technique using adaptive parameter estimation that judiciously adjusts the number of model histograms at each frame sequence is proposed. The conventional block-based background modeling method has a fixed number of background model histograms, resulting to false negatives when the image sequence has either rapid illumination changes or swiftly moving objects, and to false positives with motionless objects. In addition, the number of optimal model histogram that changes each type of input image must have found manually. We demonstrate the proposed method is promising through representative performance evaluations including the background modeling in an elevator environment that may have situations with rapid illumination changes, moving objects, and motionless objects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1487-1494
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• 2012

This paper proposes an algorithm detecting the skew of the degraded as well as the clear document images using edge and correcting it. The proposed algorithm detects edges in a character region selected by image complexity and generates projection histograms by projecting them to various directions. And then it detects the document skew by estimating the edge concentrations in the histograms and corrects the skewed document image. For the fast skew detection, the proposed algorithm uses downsampling and 3 step coarse-to-fine searching. In the skew detection of the clear and the degraded images, the maximum and the average detection errors in the proposed algorithm are about 50% of one in a conventional similar algorithm and the processing time is reduced to about 25%. In the non-uniform luminance images acquired by a mobile device, the conventional algorithm can't detect skews since it can't get valid binary images, while the proposed algorithm detect them with the average detection error of 0.1o or under.

• Journal of KIISE:Databases
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• v.30 no.2
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• pp.176-183
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• 2003

Various techniques including histograms, sampling and parametric techniques have been proposed to estimate query result sizes for the query optimization. Histogram-based techniques are the most widely used form for the selectivity estimation in relational database systems. However, in the spatio-temporal databases for the moving objects, the continual changes of the data distribution suffer the direct utilization of the state of the art histogram techniques. Specifically for the future queries, we need another methodology that considers the updated information and keeps the accuracy of the result. In this paper we propose a novel approach based upon the duality and the marginal distribution to construct a histogram with very little time since the spatio-temporal histogram requires the data distribution defined by query predicates. We use data synopsis method in the dual space to construct spatio-temporal histograms. Our method is robust to changing data distributions during a certain period of time while the objects keep the linear movements. An additional feature of our approach supports the dynamic update incrementally and maintains the accuracy of the estimated result.

• Journal of Radiation Protection and Research
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• v.43 no.2
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• pp.59-65
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• 2018

Background: We analyzed changes in the doses, structure volumes, and dose-volume histograms (DVHs) when data were transferred from one commercial treatment planning system (TPS) to another commercial TPS. Materials and Methods: A total of 22 volumetric modulated arc therapy (VMAT) plans for nasopharyngeal cancer were generated with the Eclipse system using 6-MV photon beams. The computed tomography (CT) images, dose distributions, and structure information, including the planning target volume (PTV) and organs at risk (OARs), were transferred from the Eclipse to the MRIdian system in digital imaging and communications in medicine (DICOM) format. Thereafter, DVHs of the OARs and PTVs were generated in the MRIdian system. The structure volumes, dose distributions, and DVHs were compared between the MRIdian and Eclipse systems. Results and Discussion: The dose differences between the two systems were negligible (average matching ratio for every voxel with a 0.1% dose difference criterion = $100.0{\pm}0.0%$). However, the structure volumes significantly differed between the MRIdian and Eclipse systems (volume differences of $743.21{\pm}461.91%$ for the optic chiasm and $8.98{\pm}1.98%$ for the PTV). Compared to the Eclipse system, the MRIdian system generally overestimated the structure volumes (all, p < 0.001). The DVHs that were plotted using the relative structure volumes exhibited small differences between the MRIdian and Eclipse systems. In contrast, the DVHs that were plotted using the absolute structure volumes showed large differences between the two TPSs. Conclusion: DVH interpretation between two TPSs should be performed using DVHs plotted with the absolute dose and absolute volume, rather than the relative values.