• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.12-21
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• 2006

In this paper, we propose a technique for extracting attentive objects in images using feature maps, regardless of the complexity of images and the position of objects. The proposed method uses feature maps with edge and color information in order to extract attentive objects. We also propose a reference map which is created by integrating feature maps. In order to create a reference map, feature maps which represent visually attentive regions in images are constructed. Three feature maps including edge map, CbCr map and H map are utilized. These maps contain the information about boundary regions by the difference of intensity or colors. Then the combination map which represents the meaningful boundary is created by integrating the reference map and feature maps. Since the combination map simply represents the boundary of objects we extract the candidate object regions including meaningful boundaries from the combination map. In order to extract candidate object regions, we use the convex hull algorithm. By applying a segmentation algorithm to the area of candidate regions to separate object regions and background regions, real object regions are extracted from the candidate object regions. Experiment results show that the proposed method extracts the attentive regions and attentive objects efficiently, with 84.3% Precision rate and 81.3% recall rate.

• Journal of The Korean Astronomical Society
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• v.35 no.2
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• pp.97-103
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• 2002

We have mapped 1 $deg^2$ region toward a high latitude cloud MBM 40 in the J = 1 - 0 transition of $^{12}CO$ and $^{13}CO$, using the 3 mm SIS receiver on the 14 m telescope at Taeduk Radio Astronomy Observatory. We used a high resolution autocorrelator to resolve extremely narrow CO linewidths of the molecular gas. Though the linewidth of the molecular gas is very narrow (FWHP < 1 km $s^{-1}$ ), it is found that there is an evident velocity difference between the middle upper part and the lower part of the cloud. Their spectra for both of $^{12}CO$ and $^{13}CO$ show blue wings, and the position-velocity map shows clear velocity difference of 0.4 km $s^{-1}$ between two parts. The mean velocity of the cloud is 3.1 km $s^{-1}$. It is also found that the linewidths at the blueshifted region are broader than those of the rest of the cloud. We confirmed that the visual extinction is less than 3 magnitude, and the molecular gas is translucent. We discussed three mass estimates, and took a mass of 17 solar masses from CO integrated intensity using a conversion factor $2.3 {\times} 10^{20} cm^{-2} (K\;km s^{-1})^{-1}$. Spatial coincidence and close morphological similarity is found between the CO emission and dust far-infrared (FIR) emission. The ratio between the 100 f.Lm intensity and CO integrated intensity of MBM 40 is 0.7 (MJy/sr)/(K km $s^{-1}$), which is larger than those of dark clouds, but much smaller than those of GMCs. The low ratio found for MBM 40 probably results from the absence of internal heating sources, or significant nearby external heating sources.

• Investigative Magnetic Resonance Imaging
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• v.7 no.2
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• pp.116-123
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• 2003

Purpose : The present study was undertaken to evaluate the usefulness of cerebral diffusion (DWI) and perfusion MR imaging (PWI) in rabbit models with hyperacute cerebral ischemic infarction. Materials and Methods : Experimental cerebral infarction were induced by direct injection of mixture of Histoacryl glue, lipiodol, and tungsten powder into the internal cerebral artery of 6 New-Zealand white rabbits, and they underwent conventional T1 and T2 weighted MR imaging, DWI, and PWI within 1 hour after the occlusion of internal cerebral artery. The PWI scan for each rabbit was obtained at the level of lateral ventricle and 1cm cranial to the basal ganglia. By postprocessing using special imaging software, perfusion images including cerebral blood volume (CBV), cerebral blood flow (CBF), and mean transit time (MTT) maps were obtained. The detection of infarcted lesion were evaluated on both perfusion maps and DWI. MTT difference time were measured in the perfusion defect lesion and symmetric contralateral normal cerebral hemisphere. Results : In all rabbits, there was no abnormal signal intensity on T2WI. But on DWI, abnormal high signal intensity, suggesting cerebral infarction, were detected in all rabbits. PWI (rCBV, CBF and MTT map) also showed perfusion defect in all rabbits. In four rabbits, the calculated square of perfusion defect in MTT map is larger than that of CBF map and in two rabbits, the calculated size of perfusion defect in MTT map and CBF map is same. Any rabbits do not show larger perfusion defect on CBF map than MTT map. In comparison between CBF map and DWI, 3 rabbits show larger square of lesion on CBF map than on DWI. The others shows same square of lesion on both technique. The size of lesion shown in 6 MTT map were larger than DWI. In three cases, the size of lesion shown in CBF map is equal to DWI. But these were smaller than MTT map. The calculated square of lesion in CBF map, equal to that of DWI and smaller than MTT map was three. And in one case, the calculated square of perfusion defect in MTT map was largest, and that of DWI was smallest. Conclusion : DWI and PWI may be useful in diagnosing hyperacute cerebral ischemic infarction and in e-valuating the cerebral hemodynamics in the rabbits.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.5
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• pp.213-222
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• 2008

This paper is related to color image segmentation and textile texture mapping for the 2D virtual wearing system. The proposed system is characterized as virtually wearing a new textile pattern selected by user to the clothing shape section, based on its intensity difference map, segmented from a 2D clothes model image using color image segmentation technique. Regardless of color or intensity of model clothes, the proposed system is possible to virtually change the textile pattern or color with holding the illumination and shading properties of the selected clothing shape section, and also to quickly and easily simulate, compare, and select multiple textile pattern combinations for individual styles or entire outfits. The proposed system can provide higher practicality and easy-to-use interface, as it makes real-time processing possible in various digital environment, and creates comparatively natural and realistic virtual wearing styles, and also makes semi-automatic processing possible to reduce the manual works to a minimum. According to the proposed system, it can motivate the creative activity of the designers with simulation results on the effect of textile pattern design on the appearance of clothes without manufacturing physical clothes and, as it can help the purchasers for decision-making with them, promote B2B or B2C e-commerce.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.7
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• pp.1696-1705
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• 1996

The theory of stack filtering, which is a generalization of median filtering, is used to the detection of intensity edges in noisey images. The proposed approach, called the Difference of Estimates(DoE) approach, is a new formulation of a morphological scheme which has been very sensitive to impulse noise. In this approach, stack filters are applied to a noisy image to obtain local estimates of the dilated and eroded versions of the noise-free image. Thresholding the difference between these two estimates yields the binary edge map. We find that this approach yields results comparable to those obtained with the Canny operator for images with additive Gaussian noise, burt works much better when the noise is impulsive.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.459-465
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• 2013

This paper is a study on an object extraction method which using color features of an object and background in the image. A human recognizes an object through the color difference of object and background in the image. So we must to emphasize the color's difference that apply to extraction result in this image. Therefore, we have converted to HSV color images which similar to human visual system from original RGB images, and have created two each other images that applied Median Filter and we merged two Median filtered images. And we have applied the Mean Shift algorithm which a data clustering method for clustering color features. Finally, we have normalized 3 image channels to 1 image channel for binarization process. And we have created object map through the binarization which using average value of whole pixels as a threshold. Then, have extracted major object from original image use that object map.

• Progress in Medical Physics
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• v.30 no.4
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• pp.104-111
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• 2019

Purpose: Online magnetic resonance-guided adaptive radiotherapy (MRgART), an emerging technique, is used to address the change in anatomical structures, such as treatment target region, during the treatment period. However, the electron density map used for dose calculation differs from that for daily treatment, owing to the variation in organ location and, notably, air pockets. In this study, we evaluate the dosimetric effect of electron density override on air pockets during online ART for pancreatic cancer cases. Methods: Five pancreatic cancer patients, who were treated with MRgART at the Seoul National University Hospital, were enrolled in the study. Intensity modulated radiation therapy plans were generated for each patient with 60Co beams on a ViewrayTM system, with a 45 Gy prescription dose for stereotactic body radiation therapy. During the treatment, the electron density map was modified based on the daily MR image. We recalculated the dose distribution on the plan, and the dosimetric parameters were obtained from the dose volume histograms of the planning target volume (PTV) and organs at risk. Results: The average dose difference in the PTV was 0.86Gy, and the observed difference at the maximum dose was up to 2.07 Gy. The variation in air pockets during treatment resulted in an under- or overdose in the PTV. Conclusions: We recommend the re-contouring of the air pockets to deliver an accurate radiation dose to the target in MRgART, even though it is a time-consuming method.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.1062-1075
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• 2010

In the medical image application the difference of intensity is widely used for the image segmentation and feature extraction, and a well known method is the threshold technique that determines a threshold value and generates a binary image based on the threshold. A frequently-used threshold technique is the Otsu algorithm that provides efficient processing and effective selection criterion for choosing the threshold value. However, we cannot get good segmentation results by applying the Otsu algorithm to chest X-ray images. It is because there are various organic structures around lung regions such as ribs and blood vessels, causing unclear distribution of intensity levels. To overcome the ambiguity, we propose in this paper an effective algorithm to extract pulmonary regions that utilizes the Otsu algorithm after removing the background of an X-ray image, constructs intensity-level maps, and uses them for segmenting the X-ray image. To verify the effectiveness of our method, we compared it with the existing 1-dimensional and 2-dimensional Otsu algorithms, and also the results by expert's naked eyes. The experimental result showed that our method achieved the more accurate extraction of pulmonary regions compared to the Otsu methods and showed the similar result as the naked eye's one.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.1
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• pp.1-14
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• 2021

The study has been carried out with an objective to prepare Siberian roe deer habitat potential maps in South Korea based on three geographic information system-based models including frequency ratio (FR) as a bivariate statistical approach as well as convolutional neural network (CNN) and long short-term memory (LSTM) as machine learning algorithms. According to field observations, 741 locations were reported as roe deer's habitat preferences. The dataset were divided with a proportion of 70:30 for constructing models and validation purposes. Through FR model, a total of 10 influential factors were opted for the modelling process, namely altitude, valley depth, slope height, topographic position index (TPI), topographic wetness index (TWI), normalized difference water index, drainage density, road density, radar intensity, and morphological feature. The results of variable importance analysis determined that TPI, TWI, altitude and valley depth have higher impact on predicting. Furthermore, the area under the receiver operating characteristic (ROC) curve was applied to assess the prediction accuracies of three models. The results showed that all the models almost have similar performances, but LSTM model had relatively higher prediction ability in comparison to FR and CNN models with the accuracy of 76% and 73% during the training and validation process. The obtained map of LSTM model was categorized into five classes of potentiality including very low, low, moderate, high and very high with proportions of 19.70%, 19.81%, 19.31%, 19.86%, and 21.31%, respectively. The resultant potential maps may be valuable to monitor and preserve the Siberian roe deer habitats.

• Journal of Digital Contents Society
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• v.7 no.4
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• pp.287-294
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• 2006

Mass-customization is fast growing a segment of the apparel market. 2D Virtual wearing system is one of visual support tools that make possible to sell apparel before producing and reduce the time and costs related to product development and manufacturing in the world of apparel mass-customization. This paper is related to fabric color mapping method for 2D image-based virtual wearing system. In proposed method, clothing shape section of interest is segmented from a clothes model image using a region growing method, and then mapping a new fabric color selected by user into it based on its intensity difference map is processed. With the proposed method in 2D virtual wearing system, regardless of color or intensity of model clothes, it is possible to virtually change the fabric color with holding the illumination and shading properties of the selected clothing shape section, and also to quickly and easily simulate, compare, and select multiple fabric color combinations for individual styles or entire outfits.