• The Bulletin of The Korean Astronomical Society
• /
• v.36 no.1
• /
• pp.31.1-31.1
• /
• 2011

We present wide-field near-IR imaging polarimetry of 30 Doradus in the Large Magellanic Cloud, using the InfraRed Survey Facility (IRSF). We obtained polarimetry data in J, H, and Ks bands using the JHKs-simultaneous imaging polarimeter SIRPOL. Since many Galactic field stars along the line-of-sight to the Large Magellanic Cloud are contaminated in our data, we developed methods to identify the foreground sources using the proper motion data. We investigated polarimetric properties between the Galactic foreground stars and the stars in the LMC.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.14 no.2
• /
• pp.97-102
• /
• 2019

Multi-queue I/O block layer has been recently employed in Linux kernel to support fast storage devices such as NVMe SSDs, but it lacks differentiated I/O services yet. In this paper, we propose an I/O scheduling scheme that can improve the user responsiveness of foreground processes, which are closely related to user satisfaction. To this end, we redesign the existing multi-queue block layer to classify the I/O requests from foreground processes and schedule them by exploiting the feature of NVMe interface. Experimental results show that latency and launch time of the foreground processes have been significantly improved compared to original Linux kernel.

• Proceedings of the IEEK Conference
• /
• 2001.06c
• /
• pp.77-80
• /
• 2001

In general, the informations of the inner image that user interested in are limited to a special domain. In this paper, as using Wavelet Transform for dividing image into high frequency and low frequency, We can separate foreground including many data. After calculating object boundary of separated part, We extract special features using Color Coherence Vector. According to results of this experiment, the method of comparing data extracting foreground features is more effective than comparing data extracting features of entire image when we extract the image user interested in.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.13 no.4
• /
• pp.315-321
• /
• 2009

In this paper, a level set based energy functional is proposed, the minimization of which results in simultaneous reference background image modeling and foreground segmentation. Due to the mutual constraint of the two processes, a good estimate of the background can be obtained with a small number of frames, and due to the use of the level set, an Euler-Lagrange equation that directly solves the problem can be derived.

• Journal of Korea Multimedia Society
• /
• v.16 no.11
• /
• pp.1272-1280
• /
• 2013

In this paper, we propose an audio surveillance system which can detect and localize dangerous sounds in real-time. The location information about dangerous sounds can render a PTZ camera to be directed so as to catch a snapshot image about the dangerous sound source area and send it to clients instantly. The proposed audio surveillance system firstly detects foreground sounds based on adaptive Gaussian mixture background sound model, and classifies it into one of pre-trained classes of foreground dangerous sounds. For detected dangerous sounds, a sound source localization algorithm based on Dual delay-line algorithm is applied to localize the sound sources. Finally, the proposed system renders a PTZ camera to be oriented towards the dangerous sound source region, and take a snapshot against over the sound source region. Experiment results show that the proposed system can detect foreground dangerous sounds stably and classifies the detected foreground dangerous sounds into correct classes with a precision of 79% while the sound source localization can estimate orientation of the sound source with acceptably small error.

• Journal of Crop Science and Biotechnology
• /
• v.11 no.4
• /
• pp.263-268
• /
• 2008

Bacterial leaf pustule (BLP) caused by Xanthomonas axonopodis pv. glycines is a serious disease to make pustule and chlorotic haloes in soybean [Glycine max (L). Merr.]. While inheritance mode and map positions of the BLP resistance gene, rxp are known, no sequence information of the gene was reported. In this study, we made five near isogenic lines (NILs) from separate backcrosses (BCs) of BLP-susceptible Hwangkeumkong $\times$ BLP-resistant SS2-2 (HS) and BLP-susceptible Taekwangkong$\times$ SS2-2 (TS) through foreground and background selection based on the four-stage selection strategy. First, 15 BC individuals were selected through foreground selection using the simple sequence repeat (SSR) markers Satt486 and Satt372 flanking the rxp gene. Among them, 11 BC plants showed the BLP-resistant response. The HS and TS lines chosen in foreground selection were again screened by background selection using 118 and 90 SSR markers across all chromosomes, respectively. Eventually, five individuals showing greater than 90% recurrent parent genome content were selected in both HS and TS lines. These NILs will be a unique biological material to characterize the rxp gene.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.4
• /
• pp.1712-1731
• /
• 2016

In this paper, we propose a novel saliency detection framework via multiple random walks (MRW) which simulate multiple agents on a graph simultaneously. In the MRW system, two agents, which represent the seeds of background and foreground, traverse the graph according to a transition matrix, and interact with each other to achieve a state of equilibrium. The proposed algorithm is divided into three steps. First, an initial segmentation is performed to partition an input image into homogeneous regions (i.e., superpixels) for saliency computation. Based on the regions of image, we construct a graph that the nodes correspond to the superpixels in the image, and the edges between neighboring nodes represent the similarities of the corresponding superpixels. Second, to generate the seeds of background, we first filter out one of the four boundaries that most unlikely belong to the background. The superpixels on each of the three remaining sides of the image will be labeled as the seeds of background. To generate the seeds of foreground, we utilize the center prior that foreground objects tend to appear near the image center. In last step, the seeds of foreground and background are treated as two different agents in multiple random walkers to complete the process of salient object detection. Experimental results on three benchmark databases demonstrate the proposed method performs well when it against the state-of-the-art methods in terms of accuracy and robustness.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.1
• /
• pp.157-165
• /
• 2011

It is challenging to detect foreground objects when background includes an illumination variation, shadow or structural variation due to its motion. Basically pixel-based background models including codebook-based modeling suffer from statistical randomness of each pixel. This paper proposes an algorithm that incorporates Markov random field model into pixel-based background modeling to achieve more accurate foreground detection. Under the assumptions the distance between the pixel on the input imaging and the corresponding background model and the difference between the scene estimates of the spatio-temporally neighboring pixels are exponentially distributed, a recursive approach for estimating the MRF regularizing parameters is proposed. The proposed method alternates between estimating the parameters with the intermediate foreground detection and estimating the foreground detection with the estimated parameters, after computing it with random initial parameters. Extensive experiment is conducted with several videos recorded both indoors and outdoors to compare the proposed method with the standard codebook-based algorithm.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.11 no.5
• /
• pp.487-492
• /
• 2018

Recently, various applications for image processing have been ported to the mobile environment due to the expansion of the image shooting on the mobile device. However, in the case of extracting the image foreground, which is one of the most important functions of image synthesis, is difficult since it needs complex calculation. In this paper, we propose an video synthesis technique that can divide images captured by mobile devices into foreground / background and combine them in real time on target images. Considering the characteristics of mobile shooting, our system can extract automatically foreground of input video that contains weak motion when shooting. Using SIMD and GPGPU-based acceleration algorithms, SD-quality images can be processed on mobile in real time.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.11
• /
• pp.179-186
• /
• 2009

In this paper, we propose a head detection method based on vertical and horizontal pixel histogram analysis in order to overcome drawbacks of the previous head detection approach using Haar-like feature-based face detection. In the proposed method, we create the vertical and horizontal foreground pixel histogram images from the background subtraction image, which represent the number of foreground pixels in the same vertical or horizontal position. Then we extract feature points of a head region by applying Harris corner detection method to the foreground pixel histogram images and by analyzing corner points. The proposal method shows robust head detection results even in the face image covering forelock by hairs or the back view image in which the previous approaches cannot detect the head regions.