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

• Korean Journal of Breeding Science
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• v.43 no.5
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• pp.360-367
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• 2011

Beta-carotene producing transformants were produced in the background of 'Nagdongbyeo', a Japonica rice cultivar. Introgression of the carotenoid locus in the transformant, PAC4-2 into the elite cultivar 'Ilpumbyeo' was started. To initiate a backcrossing program, we surveyed 220 SSR markers and found that 38% of them were polymorphic between 'Ilpumbyeo' as a recurrent parent and the PAC4-2 as a recipient parent. The selection strategy comprising foreground and background selection was employed. First, foreground selection was practiced in $BC_1$, $BC_2$, and $BC_3$ generations using the transgene specific PCR-based marker in addition to visual scoring of the seed color. Marker-based background selection combined with phenotypic selection was employed from $BC_3F_2$ to $BC_3F_4$ generations. Blast search indicated that the transgene PAC4-2 was located between SSR markers, RM6 and RM482. 240 $BC_3F_3$ and 63 $BC_3F_4$ lines were evaluated for four agronomic traits including days to heading. Most of the lines were similar to Ilpumbyeo in agronomic traits evaluated. The percentage of PAC4-2 genome ranged from 4% to 21% with a mean of 12.5%, which was higher than the expected for an unselected $BC_3$ backcross population. This could be explained by the fact that two genes for beta-carotene and the stripe virus resistance were targeted in this study. We selected 10 representative $BC_3F_5$ lines from 63 $BC_3F_4$ lines based on agronomic traits and carotenoids content. The selection strategy would be appropriate for the introgression of beta-carotene gene in a breeding program.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5507-5528
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• 2016

In computer vision, salient object is important to extract the useful information of foreground. With active contour analysis acting as the core in this paper, we propose a bottom-up saliency detection algorithm combining with the Bayesian model and the global color distribution. Under the supports of active contour model, a more accurate foreground can be obtained as a foundation for the Bayesian model and the global color distribution. Furthermore, we establish a contour-based selection mechanism to optimize the global-color distribution, which is an effective revising approach for the Bayesian model as well. To obtain an excellent object contour, we firstly intensify the object region in the source gray-scale image by a seed-based method. The final saliency map can be detected after weighting the color distribution to the Bayesian saliency map, after both of the two components are available. The contribution of this paper is that, comparing the Harris-based convex hull algorithm, the active contour can extract a more accurate and non-convex foreground. Moreover, the global color distribution can solve the saliency-scattered drawback of Bayesian model, by the mutual complementation. According to the detected results, the final saliency maps generated with considering the global color distribution and active contour are much-improved.

• Horticultural Science & Technology
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• v.35 no.2
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• pp.232-242
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• 2017

The goal of marker-assisted backcrossing (MAB) is to significantly reduce the number of breeding generations required by using genome-based molecular markers to select for a particular trait; however, MAB systems have only been developed for a few vegetable crops to date. Among the types of molecular markers, SNPs (single-nucleotide polymorphisms) are primarily used in the analysis of genetic diversity due to their abundance throughout most genomes. To develop a MAB system in Chinese cabbage, a high-throughput (HT) marker system was used, based on a previously developed set of 468 SNP probes (BraMAB1, Brassica Marker Assisted Backcrossing SNP 1). We selected a broad-spectrum TuMV (Turnip mosaic virus) resistance (trs) Chinese cabbage line (SB22) as a donor plant, constructing a $BC_1F_1$ population by crossing it with the TuMV-susceptible 12mo-682-1 elite line. Foreground selection was performed using the previously developed trsSCAR marker. Background selection was performed using 119 SNP markers that showed clear polymorphism between donor and recipient plants. The background genome recovery rate (% recurrent parent genome recovery; RPG) was good, with three of 75 $BC_1F_1$ plants showing a high RPG rate of over 80%. The background genotyping result and the phenotypic similarity between the recurrent parent and $BC_1F_1$ showed a correlation. The plant with the highest RPG recovery rate was backcrossed to construct the $BC_2F_1$ population. Foreground selection and background selection were performed using 169 $BC_2F_1$ plants. This study shows that, using MAB, we can recover over 90% of the background genome in only two generations, highlighting the MAB system using HT markers as a highly efficient Brassica rapa backcross breeding system. This is the first report of the application of a SNP marker set to the background selection of Chinese cabbage using HT SNP genotyping technology.

• Journal of KIISE:Information Networking
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• v.36 no.3
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• pp.198-203
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• 2009

With the growing demand for multimedia services and advances in display technology, new applications for 3$\sim$D scene communication have emerged. While multi-view video of these emerging applications may provide users with more realistic scene experience, drastic increase in the bandwidth is a major problem to solve. In this paper, we propose a fast prediction mode decision algorithm which can significantly reduce complexity and time consumption of the encoding process. This is based on the object segmentation, which can effectively identify the fast moving foreground object. As the foreground object with fast motion is more likely to be encoded in the view directional prediction mode, we can properly limit the motion compensated coding for a case in point. As a result, time savings of the proposed algorithm was up to average 45% without much loss in the quality of the image sequence.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.407-412
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• 2008

Color segmentation is one of the most challenging problems in image processing especially in case of handling the images with cluttered background. Great amount of color segmentation methods have been developed and applied to real problems. In this paper, we suggest a new methodology. Our approach is focused on background extraction, as a complimentary operation to standard foreground object segmentation, using self-organizing feature selective property of unsupervised self-learning paradigm based on the competitive algorithm. The results of our studies show that background segmentation can be achievable in efficient manner.

• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.67-72
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• 2005

Most of image binarization algorithms analyzes the intensity distribution using the histogram for the determination of threshold value. When the intensity difference between the foreground object and the background is great, the histogram shows the tendency to be bimodal and the selection of the histogram valley as the threshold value shows the good result. On the other side. when the intensity difference is not great and the histogram doesn't show the bimodal property, the histogram analysis doesn't support the selection of the proper threshold value. This Paper Proposed the novel binarization method that applies the fuzzy membership function to each color value on the RGB color model and, by using the operation results, separates the features having the great readability from the background. The proposed method prevents the loss of information incurred by the gray scale conversion by using the RGB color model and extracts effectively the readable features by using the fuzzy inference Compared with the traditional binarization methods, the proposed method is able to remove the majority of noise areas and show the improved results on the image of transport containers , etc.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.53-68
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• 2011

A selection of viewpoint is a first priority for landscape evaluation. However, it has been artificially carried out by a subjective method without of criterion. Therefore, this study proposed the objective and quantitative viewpoint selection methods using space syntax and GIS. For this, the study area on samduk3 residential improvement district located at Daegu city was divided into 24 sectors of visibility zone by distance and direction. After that, the preliminary viewpoints equally distributed in space were selected by axial map analysis of space syntax and viewshed-frequency analysis of GIS. According to the result of selection of the final viewpoints using the VEI(Viewpoint Evaluation Index), all the final viewpoints were placed in the National Debt Repayment Movement; VEI value of VP-2 was 112.63 in the foreground, VP-10 was 18.31 in the middleground and VP-18 was 5.55 in the background. Selected viewpoints were verified as a big changing of landscape variation and high chance of view such as the public area, the park and the high-density residential area. Thus, VEI will be used as a quantitative method of selecting viewpoints and it is expected to be able to use as the objective indicator.

• Horticultural Science & Technology
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• v.35 no.4
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• pp.465-479
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• 2017

Chili pepper (Capsicum annuum L.) is an economically important horticultural crop in Korea; however, various diseases, including Phytophthora root rot, anthracnose, powdery mildew, Cucumber mosaic virus (CMV), Pepper mild mottle virus (PMMoV), and Pepper mottle virus (PepMoV), severely affect their productivity and quality. Therefore, pepper varieties with resistance to multiple diseases are highly desired. In this study, we developed 20 SNP type assays for three pepper populations using Fluidigm nanofluidic dynamic arrays. A total of 4,608 data points can be produced with a 192.24 dynamic array consisting of 192 samples and 24 SNP markers. The assays were converted from previously developed sequence-tagged-site (STS) markers and included markers for resistance to Phytophthora root rot (M3-2 and M3-3), anthracnose (CcR9, CA09g12180, CA09g19170, CA12g17210, and CA12g19240), powdery mildew (Ltr4.1-40344, Ltr4.2-56301, and Ltr4.2-585119), bacterial spot (Bs2), CMV (Cmr1-2), PMMoV (L4), and PepMoV (pvr1 and pvr2-123457), as well as for capsaicinoids content (qcap3.1-40134, qcap6.1-299931, qcap6.1-589160, qdhc2.1-1335057, and qdhc2.2-43829). In addition, 11 assays were validated through a comparison with the corresponding data of the STS markers. Furthermore, we successfully applied the assays to commercial $F_1$ cultivars and to our breeding lines. These 20 SNP type assays will be very useful for developing new superior pepper varieties with resistance to multiple diseases and a higher content of capsaicinoids for increased pungency.

• Journal of The Korean Astronomical Society
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• v.56 no.1
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• pp.97-115
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• 2023

We present the deep homogeneous UBV RI photometric data of 135,071 stars down to V ~ 23 mag and I ~ 22 mag toward the Carina Nebula. These stars are cross-matched with those from the previous surveys in the X-ray, near-infrared, and mid-infrared wavelengths as well as the Gaia Early Data Release 3 (EDR3). This master catalog allows us to select reliable members and determine the fundamental parameters distance, size, stellar density of stellar clusters in this star-forming region. We revisit the reddening toward the nebula using the optical and the near-infrared colors of early-type stars. The foreground reddening [E(B-V)_fg] is determined to be 0.35 ± 0.02, and it seems to follow the standard reddening law. On the other hand, the total-to-selective extinction ratio of the intracluster medium (R_V,cl) decreases from the central region (Trumpler 14 and 16, R_V,cl ~ 4.5) to the northern region (Trumpler 15, R_V,cl ~ 3.4). It implies that the central region is more dusty than the northern region. We find that the distance modulus of the Carina Nebula to be 11.9 ± 0.3 mag (d = 2.4 ± 0.35 kpc) using a zero-age main-sequence fitting method, which is in good agreement with that derived from the Gaia EDR3 parallaxes. We also present the catalog of 3,331 pre-main-sequence (PMS) members and 14,974 PMS candidates down to V ~ 22 mag based on spectrophotometric properties of young stars at infrared, optical, and X-ray wavelengths. From the spatial distribution of PMS members and PMS candidates, we confirm that the member selection is very reliable down to faint stars. Our data will have a legacy value for follow-up studies with different scientific purposes.