• Journal of IKEEE
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• v.16 no.4
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• pp.349-355
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• 2012

Information technology improves convenience, safety, and performance of automobiles. Recently, a lot of algorithms are studied to provide safety and environment information for driving, and lane detection algorithm is one of them. In this paper, we propose a lane detection algorithm that reduces the amount of calculation by reducing region of interest (ROI) after preprocessing. The proposed algorithm reduces the area of ROI a lot by determining the candidate regions near lane boundaries as V-ROI so that the amount of calculation is reduced. In addition, the amount of calculation can be maintained almost the same regardless of the resolutions of the input images by compressing the images since the lane detection algorithm does not require high resolution. The proposed algorithm is implemented using C++ and OpenCV library and is verified to work at 30 fps for realtime operation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.634-640
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• 2018

In this paper, we propose an automatic extraction algorithm of region of interest(ROI) based on medical x-ray images. The proposed algorithm uses segmentation, feature extraction, and reference image matching to detect lesion sites in the input image. The extracted region is searched for matching lesion images in the reference DB, and the matched results are automatically extracted using the Kalman filter based fitness feedback. The proposed algorithm is extracts the contour of the left hand image for extract growth plate based on the left x-ray input image. It creates a candidate region using multi scale Hessian-matrix based sessionization. As a result, the proposed algorithm was able to split rapidly in 0.02 seconds during the ROI segmentation phase, also when extracting ROI based on segmented image 0.53, the reinforcement phase was able to perform very accurate image segmentation in 0.49 seconds.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.511-520
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• 2016

Automatic License Plate Detection (ALPD) is a key technology for a efficient traffic control. It is used to improve work efficiency in many applications such as toll payment systems and parking and traffic management. Until recently, the hand-crafted features made for image processing are used to detect license plates in most studies. It has the advantage in speed. but can degrade the detection rate with respect to various environmental changes. In this paper, we propose a way to utilize a Faster Region based Convolutional Neural Networks (Faster R-CNN) and a Conventional Convolutional Neural Networks (CNN), which improves the computational speed and is robust against changed environments. The module based on Faster R-CNN is used to detect license plate candidate regions from images and is followed by the module based on CNN to remove False Positives from the candidates. As a result, we achieved a detection rate of 99.94% from images captured under various environments. In addition, the average operating speed is 80ms/image. We implemented a fast and robust Real-Time License Plate Detection System.

• Journal of the Korean Society of Radiology
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• v.12 no.6
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• pp.707-712
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• 2018

The number of CT examinations is increasing, and radiation exposure is also increasing. repeated tests can affect the lens and thyroid. In hospitals, there is a tendency to lack interest in major long-term radiation exposure compared to the interest in increasing image information and image quality with head CT. In this study, we analyzed the improvement of image quality by proposed method to the noisy CT images. The proposed denoising method total variance optimization only for the impulsive noise candidate pixels. Experimental results show that edge information is well preserved and impulse noise can be effectively removed. and worked very well for the images according to tube voltage and rotation time. applied to the clinical setting, it can be used as the lowest exposure condition without worrying about the image quality and it will be helpful for the CT application.

• BMB Reports
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• v.48 no.5
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• pp.271-276
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• 2015

Baicalin is a flavonoid derived from the dried root of Scutellaria baicalensis. In this study, oxygen-induced retinopathy was used to characterize the anti-angiogenic properties of baicalin in mice. Pups were exposed to a hyperbaric oxygen environment to induce retinal angiogenesis and were subjected to intraperitoneal injection of baicalin. Avascular area, neovascular tufts, and neovascular lumens were quantified from digital images. Compared to the vehicle, baicalin clearly reduced the central avascular zone and the number of neovascular tufts and lumens. High-dose baicalin (10 mg/kg) significantly reduced the expression of matrix metalloproteinase-2 (MMP-2), MMP-9, angiotensin II, and vascular endothelial growth factor (VEGF). These results show that baicalin is a powerful antiangiogenic compound that attenuates new vessel formation in the retina after systemic administration, and is a candidate substance for therapeutic inhibition of retinal angiogenesis. [BMB Reports 2015; 48(5): 271-276]

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.21-24
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• 2001

In this paper, we present a fast face detection algorithm by estimating the eye region using neural network. To implement a real time face detection system, it is necessary to reduce search space. We limit the search space just to a few pairs of eye candidates. For the selection of them, we first isolate possible eye regions in the fast and robust way by modified histogram equalization. The eye candidates are paired to form an eye pair and each of the eye pair is estimated how close it is to a true eye pair in two aspects : One is how similar the two eye candidates are in shape and the other is how close each of them is to a true eye image A multi-layer perceptron neural network is used to find the eye candidate region's closeness to the true eye image. Just a few best candidates are then verified by eigenfaces. The experimental results show that this approach is fast and reliable. We achieved 94% detection rate with average 0.1 sec Processing time in Pentium III PC in the experiment on 424 gray scale images from MIT, Yale, and Yonsei databases.

• The Journal of the Acoustical Society of Korea
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• v.23 no.1
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• pp.40-46
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• 2004

The equivalent source method (ESM) uses two groups of equivalent source positions. One group includes the first order images of the sound source inside the enclosure. The positions of the other group are usually on a spherical surface some distance outside the enclosure. A proper selection of the positions for the far field sources could greatly improve the performance of the modeling accuracy and reduce the number of the sources to achieve the required accuracy. This study uses optimally distributed far field source positions on the surface of enlarged version of the rectangular enclosure instead of using typical spherical distribution. Simulations using various sizes of the box shaped distribution are executed and optimal positions are searched using an optimization technique from the larger number of candidate positions. The results of using these far field source positions are compared and analyzed.

• Journal of The Korean Astronomical Society
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• v.42 no.5
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• pp.125-134
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• 2009

We investigated the circumnuclear region of the Seyfert 2 galaxy NGC 5728, using the CFHT 3.6 m OASIS $[S_{II}]$, $[O_{III}]$ & $H\beta$ spectral images complemented with the IUE spectra. The physical condition of the circumnuclear zone has been derived: the gas density (indicated by $[S_{II}]$6716/31 ratio) around the C core is generally similar to that around the NW core, i.e., $\sim500cm^{-3}$. However, there appears to be evidence of a higher density shell in front of the NW core, $\sim10^4cm^{-3}$ at -250 km $s^-1$. The IUE $Si_{III}$]1892/$C_{III}$]1909 ratio implies a possible presence of a broad emission region of gas densities of $\sim10^{10}cm^{-3}$. The SE cone and surrounding area show several prominent features, while the NW cone does not show any particular structure: we identified three prominent blobs in the SE cone and one possible candidate in the NW cone. The outflow activities exist within the relatively large conic opening angle. We discussed the possibility of inflow or outflow activities of blobs found in the circumnuclear region of NGC 5728. The gas around two cores, two cones, and several blobs, is likely to be excited by the AGN hot source(s).

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.69.1-69.1
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• 2013

We describe a survey of quasars in the early universe beyond z=5, which is one of the main sciences of the Infrared Medium-deep Survey (IMS) performed by the Center for the Exploration of the Origin of the Universe (CEOU). We use multi-wavelength archival data such as SDSS, CFHTLS, UKIDSS, and SWIRE, which provide deep images over wide areas sufficient enough for searching high redshift quasars. In addition, we carried out a J-band imaging survey at the United Kingdom InfraRed Telescope (UKIRT) with a depth of ~23 AB and survey area of ~100 $deg^2$, which makes IMS the most suitable survey for finding high redshift quasars at z~7. Also for the quasar candidates at z~5.5, we are conducting observations with the Camera for QUasars in EArly uNiverse (CQUEAN), which are efficient for selecting robust quasar candidate samples in this redshift range. We used various color-color diagrams suitable to the specific redshift ranges, which can reduce the contaminating sources such as M/L/T dwarfs, low redshift galaxies, and instrumental defects. The high redshift quasars we are confirming can provide us with clues to the growth of super massive black holes since z~7. Also by expanding the quasar sample at 5

• International Journal of Automotive Technology
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• v.8 no.4
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• pp.493-504
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• 2007

This paper proposes a stereo vision-based forward obstacle detection and distance measurement method. In general, stereo vision-based obstacle detection methods in automotive applications can be classified into two categories: IPM (Inverse Perspective Mapping)-based and disparity histogram-based. The existing disparity histogram-based method was developed for stop-and-go applications. The proposed method extends the scope of the disparity histogram-based method to highway applications by 1) replacing the fixed rectangular ROI (Region Of Interest) with the traveling lane-based ROI, and 2) replacing the peak detection with a constant threshold with peak detection using the threshold-line and peakness evaluation. In order to increase the true positive rate while decreasing the false positive rate, multiple candidate peaks were generated and then verified by the edge feature correlation method. By testing the proposed method with images captured on the highway, it was shown that the proposed method was able to overcome problems in previous implementations while being applied successfully to highway collision warning/avoidance conditions, In addition, comparisons with laser radar showed that vision sensors with a wider FOV (Field Of View) provided faster responses to cutting-in vehicles. Finally, we integrated the proposed method into a longitudinal collision avoidance system. Experimental results showed that activated braking by risk assessment using the state of the ego-vehicle and measuring the distance to upcoming obstacles could successfully prevent collisions.