• The Plant Pathology Journal
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• v.31 no.2
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• pp.152-164
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• 2015

Biological control of major rice diseases has been attempted in several rice-growing countries in Asia during the last few decades and its application using antagonistic bacteria has proved to be somewhat successful for controlling various fungal diseases in field trials. Two novel endophytic Bacillus species, designated strains YC7007 and $YC7010^T$, with antimicrobial, plant growth-promoting, and systemic resistance-inducing activities were isolated from the roots of rice in paddy fields at Jinju, Korea, and their multifunctional activities were analyzed. Strain YC7007 inhibited mycelial growth of major rice fungal pathogens strongly in vitro. Bacterial blight and panicle blight caused by Xanthomonas oryzae pv. oryzae (KACC 10208) and Burkholderia glumae (KACC 44022), respectively, were also suppressed effectively by drenching a bacterial suspension ($10^7cfu/ml$) of strain YC7007 on the rhizosphere of rice. Additionally, strain YC7007 promoted the growth of rice seedlings with higher germination rates and more tillers than the untreated control. The taxonomic position of the strains was also investigated. Phylogenetic analyses based on 16S rRNA gene sequences indicated that both strains belong to the genus Bacillus, with high similarity to the closely related strains, Bacillus siamensis KACC $15859^T$ (99.67%), Bacillus methylotrophicus KACC $13105^T$ (99.65%), Bacillus amyloliquefaciens subsp. plantarum KACC $17177^T$ (99.60%), and Bacillus tequilensis KACC $15944^T$ (99.45%). The DNA-DNA relatedness value between strain $YC7010^T$ and the most closely related strain, B. siamensis KACC $15859^T$ was $50.4{\pm}3.5%$, but it was $91.5{\pm}11.0%$ between two strains YC7007 and $YC7010^T$, indicating the same species. The major fatty acids of two strains were anteiso-$C_{15:0}$ and iso $C_{15:0}$. Both strains contained MK-7 as a major respiratory quinone system. The G+C contents of the genomic DNA of two strains were 50.5 mol% and 51.2 mol%, respectively. Based on these polyphasic studies, the two strains YC7007 and $YC7010^T$ represent novel species of the genus Bacillus, for which the name Bacillus oryzicola sp. nov. is proposed. The type strain is $YC7010^T$ (= KACC $18228^T$). Taken together, our findings suggest that novel endophytic Bacillus strains can be used for the biological control of rice diseases.

• Bulletin of the Korean Chemical Society
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• v.18 no.2
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• pp.193-197
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• 1997

Theoretical studies on the base-catalyzed deprotonation of 4-phenacylpyridinium cations, R1-CO-CH2-C5H4N-R2, I (R1=YC6H4 -and R2=CH3), and II (R1=C6H5 and R2=CH2C6H4Y) have been carried out with bases, NH3 and XC6H4NH2 using AM1 MO method. The Brψnsted α values are 0.20 and 0.22 and the βB values are 0.62 and 0.61, respectively for cations I and II. The negative Ⅰ (=α-βB) values obtained are in accord with the experimental results in aqueous solution, although the theoretical gas-phase α values for I are somewhat smaller than the experimental values in water due to neglect of solvation effect. It has been stressed that the Brψnsted α is distorted not only by the lag in the resonance and solvation development in the carbanion, but also by the difference in the distance between the anionic center and substituents in the TS and in the product anion.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1828-1834
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• 2007

This study proposes a new digital watermarking technique based on wavelet transformation on color image. First the $YC_bC_r$ coordinates obtain from RGB color space. then, the correlation of watermark is decreased by Arnold transformation. Next, watermark which has been enlarged by Linear Bit-expansion is inserted at a given intensity in Color images' low frequency sub-bands. When detecting the presence of watermark, F-norm function is applied. As a result of the various experiments on color images, the proposed watermarking technique has outstanding quality in regards to fidelity and robustness.

• Food Science of Animal Resources
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• v.25 no.3
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• pp.295-303
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• 2005

A total of 120 pigs were used to investigate the effect of feeding probiotics on physico-chemical properties and sensory evaluation of pork loin. About 50kg pigs were randomly alloted into one of six experimental diet groups (C1:commercial diet feed the gilt; C2:commercial diet feed the barrow; T1:$0.5\%$ YC2000 feed the gilt T2:$0.5\%$ YC2000 feed the barrow; T3:$0.1\%$ YC2000 + $0.3\%$ KBC1121 feed the gilt; T4:$0.1\%$ YC2000 + $0.3\%$ KBC1121 feed the barrow). Pigs were slaughtered at approximately 110kg live weight. Crude fat and crude ash were not difference among the treatments. However, water content was higher in T1 and T2 compared to other treatment and the protein level of T3 was higher than those of other treatments. All of dietary probiotic groups showed higher pH compared to control. Especially, pH of T1 and T2 were higher among the dietary probiotic groups. Cholesterol level of dietary probiotic groups were lower compared to control. In meat color, $a^{*}$ was higher in T1 and $b^{*}$ was lower in T2 compared to other treatments. In sensory evaluation of cooked meat, aroma, flavor, tenderness, juiciness and overall palatability were higher in control, whereas T3 and T4 showed higher score in tenderness, juiciness and overall palatability. T3 had higher myristic acid. palmitoleic acid and oleic acid, whereas arachidonic acid was lower in T3. In conclusion, dietary probiotic groups were much better than other treatments in cholesterol, color, tenderness and juiciness. But drip loss of dietary probiotic groups showed higher due to lower pH compared to control.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.255-262
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• 2007

This paper proposes an enhanced skin color-based detection method to find a region of human face in color images. The proposed detection method combines three color spaces, RGB, $YC_bC_r$, YIQ and builds color union histograms of luminance and chrominance components respectively. Combined color union histograms are then fed in to the back-propagation neural network for training and Levenberg-Marquadt algorithm is applied to the iteration process of training. Proposed method with Levenberg-Marquadt algorithm applied to training process of neural network contributes to solve a local minimum problem of back-propagation neural network, one of common methods of training for face detection, and lead to make lower a detection error rate. Further, proposed color-based detection method using combined color union histograms which give emphasis to chrominance components divided from luminance components inputs more confident values at the neural network and shows higher detection accuracy in comparison to the histogram of single color space. The experiments show that these approaches perform a good capability for face region detection, and these are robust to illumination conditions.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1591-1600
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• 2007

Camera position information from 2D face image is very important for that make the virtual 3D face model synchronize to the real face at view point, and it is also very important for any other uses such as: human computer interface (face mouth), automatic camera control etc. We present an algorithm to detect human face region and mouth, based on special color features of face and mouth in $YC_bC_r$ color space. The algorithm constructs a mouth feature image based on $C_b\;and\;C_r$ values, and use pattern method to detect the mouth position. And then we use the geometrical relationship between mouth position information and face side boundary information to determine the camera position. Experimental results demonstrate the validity of the proposed algorithm and the Correct Determination Rate is accredited for applying it into practice.

• Journal of IKEEE
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• v.2 no.2 s.3
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• pp.185-193
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• 1998

Fractal-based monochrome image coding method can be easily applied for color image compression by splitting the color image into different primary spectral channels such as RGB, YIQ or $YC_bC_r$, and encoding each channel independently According to this method, it needs to repeat the fractal coding for each channel, so it have the problem of encoding time. In this paper, a fractal-based coder for color still image is proposed which features the enhancement of compression rate and the reduction of coding time. As the result of the experiment where the proposed algorithm is applied far color images, the compression rate is enhanced by 28 : 1 above with average PSNR value $28{\sim}29[dB]$, do not lossless encoding process using JPEG. And the encoding time is reduced by maximum 11.5 %.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.89-92
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• 2000

본 논문에서는 웨이블릿 변환과 확산코드를 이용하여 동영상 내부에 이진이미지패턴형 워터마크를 삽입할 수 있는 새로운 워터마킹 방법을 소개한다. 먼저, 동영상을 디코딩하여 RGB 데이터로 이루어진 인트라 프레임(I-frame)들을 구한다. 그리고 이것을 YC$_{b}$C$_{r}$ 좌표공간으로 변환한 후, 휘도 평면만을 3단계 DWT하여 확산코드와 다중가중치를 조합한 워터마크를 삽입한다. 실험에서는 제안한 방법으로 워터마킹된 영상의 화질을 기존의 방법들과 비교하고, 손실압축과 밝기(brightness)변화 그리고 대비(contrast)실험 등을 통해 제안한 방법의 견고성을 입증해 보인다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.805-808
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• 2004

본 논문에서는 컬러정보를 이용하여 외부 조명의 영향에 대응하면서 얼굴 후보영역을 추출하고, 추출된 후보 영역으로부터 다채널 스킨컬러 모델로 특정 정보를 추출하는 검출 기법을 제시한다. 외부 조명에 민감한 스킨컬러 특성을 고려해 색상정보와 광도를 분리할 수 있는 $YC_rC_b$ 색상모델을 이용하며, Green, Blue 채널의 정보를 Gaussian 확률밀도 모델로부터 $C_b-C_g$의 좁은 범위에 분포되어 있는 스킨컬러 영역 밀도를 모델링한다. 또한 얼굴영역에 Region Restricting과 임계값 반복 알고리즘을 사용하여 눈 영역 검출 과정을 보이고, 실시간 복합 얼굴 검출 시스템 조명방식에 의해 결과를 나타낸다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.697-704
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• 2018

Since the face in image content corresponds to individual information that can distinguish a specific person from other people, it is important to accurately detect faces not hidden in an image. In this paper, we propose a method to accurately detect a face from input images using a deep learning algorithm, which is one of the machine learning methods. In the proposed method, image input via the red-green-blue (RGB) color model is first changed to the luminance-chroma: blue-chroma: red-chroma ($YC_bC_r$) color model; then, other regions are removed using the learned skin color model, and only the skin regions are segmented. A CNN model-based deep learning algorithm is then applied to robustly detect only the face region from the input image. Experimental results show that the proposed method more efficiently segments facial regions from input images. The proposed face area-detection method is expected to be useful in practical applications related to multimedia and shape recognition.