• 한국균학회소식:학술대회논문집
• /
• 2015.05a
• /
• pp.29-29
• /
• 2015

Clubroot disease is caused by the soil-born obligate plant pathogen Plasmodiophora brassicae. This pathogen can infect all cruciferous vegetables and oil crops, including Brassica rapa, B. oleracea, B. napus, and other Brassica species. Clubroot disease is now considered to be a major problem in Chinese cabbage production in China, Korea, and Japan. We collected several hundreds of P. brassicae infected galls from Korea, and isolated the single spore from the collection. For establishment of novel isolation, and mass-propagation methods for singe spore isolates of P. brassicae pathogen, we developed new filtration method using both cellulose nitrate filter and syringe filter. Accurate detection of P. brassicae pathogen in the field was done by using real-time PCR in the potential infested soil. When we tested the different pathogenicity on commercial Chinese cabbage varieties, P. brassicae from collected galls showed various morphological patterns about clubroot symptom on roots. To date, 8 CR loci have been identified in the B. rapa genome using the quantitative trait loci (QTL) mapping approach, with different resistant sources and isolates. We are trying to develop the molecular marker systems for detect all 8 CR resistant genes. Especially for the study on the interaction between pathogens and CR loci which are not well understood until now, genome wide association studies are doing using the sequenced inbred lines of Chinese cabbage to detect the novel CR genes.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.11
• /
• pp.5624-5638
• /
• 2016

A novel method based on Surf points is proposed to detect and lock-track single ground target in aerial videos. Videos captured by moving cameras contain complex motions, which bring difficulty in moving object detection. Our approach contains three parts: moving target template detection, search area estimation and target tracking. Global motion estimation and compensation are first made by grids-sampling Surf points selecting and matching. And then, the single ground target is detected by joint spatial-temporal information processing. The temporal process is made by calculating difference between compensated reference and current image and the spatial process is implementing morphological operations and adaptive binarization. The second part improves KALMAN filter with surf points scale information to predict target position and search area adaptively. Lastly, the local Surf points of target template are matched in this search region to realize target tracking. The long-term tracking is updated following target scaling, occlusion and large deformation. Experimental results show that the algorithm can correctly detect small moving target in dynamic scenes with complex motions. It is robust to vehicle dithering and target scale changing, rotation, especially partial occlusion or temporal complete occlusion. Comparing with traditional algorithms, our method enables real time operation, processing $520{\times}390$ frames at around 15fps.

• Journal of the Korean Society for Precision Engineering
• /
• v.31 no.3
• /
• pp.233-241
• /
• 2014

This paper contributes to development of a new method for detecting rear-side vehicles and estimating the positions for blind spot region or providing the lane change information by using vision systems. Because the real image acquired during car driving has a lot of information including the target vehicle and background image as well as the noises such as lighting and shading, it is hard to extract only the target vehicle against the background image with satisfied robustness. In this paper, the target vehicle has been detected by repetitive image processing such as sobel and morphological operations and a Kalman filter has been also designed to cancel the background image and prevent the misreading of the target image. The proposed method can get faster image processing and more robustness rather than the previous researches. Various experiments were performed on the highway driving situations to evaluate the performance of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.11
• /
• pp.4395-4412
• /
• 2020

The multisource image fusion has become an active topic in the last few years owing to its higher segmentation rate. To enhance the accuracy of multimodal pig-body feature segmentation, a multisource image fusion method was employed. Nevertheless, the conventional multisource image fusion methods can not extract superior contrast and abundant details of fused image. To superior segment shape feature and detect temperature feature, a new multisource image fusion method was presented and entitled as NSST-GF-IPCNN. Firstly, the multisource images were resolved into a range of multiscale and multidirectional subbands by Nonsubsampled Shearlet Transform (NSST). Then, to superior describe fine-scale texture and edge information, even-symmetrical Gabor filter and Improved Pulse Coupled Neural Network (IPCNN) were used to fuse low and high-frequency subbands, respectively. Next, the fused coefficients were reconstructed into a fusion image using inverse NSST. Finally, the shape feature was extracted using automatic threshold algorithm and optimized using morphological operation. Nevertheless, the highest temperature of pig-body was gained in view of segmentation results. Experiments revealed that the presented fusion algorithm was able to realize 2.102-4.066% higher average accuracy rate than the traditional algorithms and also enhanced efficiency.

• Journal of Digital Contents Society
• /
• v.19 no.6
• /
• pp.1207-1212
• /
• 2018

The ultrasound image uses ultrasonic pulses to receive the reflected waves and construct an image necessary for diagnosis. At this time, when the signal becomes weak, noise is generated and a slight difference in brightness occurs. In addition, fluctuation of image due to breathing phenomenon, which is the characteristic of ultrasound image, and change of motion in real time occurs. Such a noise is difficult to recognize and diagnose visually in the analysis process. In this paper, morphological features are automatically extracted by using image processing technique on ultrasound acquired images. In this paper, we implemented a GPU - based fast filter using a cloud big data processing platform for image processing. In applying the GPU - based high - performance filter, the algorithm was run with performance 4.7 times faster than CPU - based and the PSNR was 37.2dB, which is very similar to the original.

• Journal of The Korean Astronomical Society
• /
• v.46 no.5
• /
• pp.191-200
• /
• 2013

Full-disk solar images are provided by many solar telescopes around the world. However, the observed images show Non-Radial Variation (NRV) over the disk. In this paper, we propose algorithms for detecting distortions and restoring these images. For detecting NRV, the cross-correlation coefficients matrix of radial profiles is calculated and the minimum value in the matrix is defined as the Index of Non-radial Variation (INV). This index has been utilized to evaluate the H images of GONG, and systemic variations of different instruments are obtained. For obtaining the NRV's image, a Multi-level Morphological Filter (MMF) is designed to eliminate structures produced by solar activities over the solar surface. Comparing with the median filter, the proposed filter is a better choice. The experimental results show that the effect of our automatic detection and restoration methods is significant for getting a flat and high contrast full-disk image. For investigating the effect of our method on solar features, structural similarity (SSIM) index is utilized. The high SSIM indices (close to 1) of solar features show that the details of the structures remain after NRV restoring.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2007.04a
• /
• pp.315-319
• /
• 2007

This paper presents a algorithm, what is able to recognize 4 different continuous human motion using a single stationary camera as input. For the first step, we acquire images from a camera. To enhance the image, we perform preprocessing which deals with removing noise using median filter, thresholding. And then morphological operations are performed to remove which small blobs and eliminates small holes. At the forth step, blobs are analysed to extracts for foreground region. Then, motions are predicted from these images by using optical flow technique, and the predicted motion data are refined by comparing our cardboard models so as to judge behavior pattern.

• Microbiology and Biotechnology Letters
• /
• v.14 no.5
• /
• pp.377-383
• /
• 1986

About 300 cellulolytic actinomycetes isolated from soils were tested for their cellulase activities estimated by means of filter paper swelling and carboxymethyl cellulose saccharifying activity. Then, 16 isolates which had shown relatively high levels of CMCase activity were selected and examined for their abilities of $\beta$-glucosidase production. Among them strain No. 109 was found to have highest level of intracellular $\beta$-glucosidase, and selected for the further studies. In this paper, the cultural, morphological and physiological properties, and cell wall composition of strain No. 109 were described in relation to the taxonomic status of this actinomycete. Based on the results obtained in these experiments strain No. 109 was identified to be a similar species to Streptomyces tanashiensis.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.6B
• /
• pp.1012-1020
• /
• 2000

In this paper, This paper presents a new algorithm which is used for detecting and extracting human masks from a color still image. The regions where each pixel has a value of skin-color were extracted from the Cb and Cr images, after the tone of the color image is converted to YCbCr from. A morphological filter is used to eliminate noise in the resulting image. By scanning it in horizontal and vertical ways under ways under threshold value, first candidate section is chosen. If it is not a face, secondary candidate section is taken and is divided into two candidate sections. The proposed algorithm is not affected by the variation of illuminations, because it uses only Cb and Cr components in YCbCr color format. Moreover, the face recognition was possible regardless of the degree of shifting face, changed shape, various sizes of the face, and the quality of image.

• Proceedings of the Korean Information Science Society Conference
• /
• 2001.10b
• /
• pp.481-483
• /
• 2001

최근 전자제품의 초소형화에 따라, PCB 기판위의 부품의 집적도를 높이기 위해, 기존의 리드대신 부품 밑면에 볼(ball)이 격자형태로 배열되어 있는 BGA(Ball Grid Array) 형태의 팩키지가 많이 사용되고 있다. 하지만, BGA의 구조상 한번 장착되면 외관검사가 불가능하므로, 장착전 BGA의 검사가 필수적이다. BGA의 검사항목중 가장 중요한 항목인 볼 높이검사를 실시간으로 하기 위해서는 고속 비접촉 3차원 측정기술이 요구된다. 본 논문에서는 일반카메라보다 100배이상 높이 프로파일 취득속도가 빠른 3D smart camera와 레이저 슬릿광(slit ray)을 이용하여 고속으로 BGA 볼의 3D 프로파일을 얻은 후, clipping과 morphological filter를 사용하여 인접한 볼표면에서의 난반사로 인한 에러 데이터를 보정하여 정확한 3D 영상을 취득할 수 있는 시스템을 소개한다.