• Proceedings of the Korea Concrete Institute Conference
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• 2008.04a
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• pp.1009-1012
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• 2008

The fiber dispersion performance in fiber-reinforced cementitious composites is a crucial factor with respect to achieving desired mechanical performance. However, evaluation of the fiber dispersion performance in the composite PVA-ECC(Polyvinyl alcohol-Engineered Cementitious Composite) is extremely challenging because of the low contrast of PVA fibers with the cement-based matrix. In the present work, an enhanced fiber detection technique is developed and demonstrated. Using a fluorescence technique on the PVA-ECC, PVA fibers are observed as green dots in the cross-section of the composite. After capturing the fluorescence image with a Charged Couple Device(CCD) camera through a microscope. The fibers are more accurately detected by employing a series of process based on a categorization, watershed segmentation, and morphological reconstruction.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.610-616
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• 2012

In this paper, we present a method to detect an object such as ship, rock and buoy from sea IR image for the safety navigation. To this end, we do the image smoothing first and the apply watershed algorithm to segment image into subregions. Since watershed algorithm almost always produces over-segmented regions, it requires posterior merging process to get meaningful segmented regions. We propose an efficient merger algorithm that requires only two times of direct access to the pixels regardless of the number of regions. Also by analyzing IR image obtained from sea environments, we could find out that most horizontal edge come out from object regions. For the given input IR image we extract horizontal edge and eliminate isolated edges produced from background and noises by adopting morphological operator. Among the segmented regions, the regions that have horizontal edges are extracted as final results. Experimental results show the adequacy of the proposed method.

• Journal of Digital Contents Society
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• v.13 no.2
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• pp.235-245
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• 2012

This paper introduce a quiz game contents based on gesture interface. We analyzed the off-line quiz games, extracted its presiding components, and digitalized them so that the proposed game contents is able to substitute for the off-line quiz games. We used the Kinect camera to obtain the depth images and performed the preprocessing including vertical human segmentation, head detection and tracking and hand detection, and gesture recognition for hand-up, hand vertical movement, fist shape, pass and fist-and-attraction. Especially, we defined the interface gestures designed as a metaphor for natural gestures in real world so that users are able to feel abstract concept of movement, selection and confirmation tangibly. Compared to our previous work, we added the card compensation process for completeness, improved the vertical hand movement and the fist shape recognition methods for the example selection and presented an organized test to measure the recognition performance. The implemented quiz application program was tested in real time and showed very satisfactory gesture recognition results.

• Korean Journal of Agricultural Science
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• v.47 no.2
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• pp.205-217
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• 2020

In this study, a deep learning-based tillage boundary detection method for autonomous tillage by a tractor was developed, which consisted of image cropping, object classification, area segmentation, and boundary detection methods. Full HD (1920 × 1080) images were obtained using a RGB camera installed on the hood of a tractor and were cropped to 112 × 112 size images to generate a dataset for training the classification model. The classification model was constructed based on convolutional neural networks, and the path boundary was detected using a probability map, which was generated by the integration of softmax outputs. The results show that the F1-score of the classification was approximately 0.91, and it had a similar performance as the deep learning-based classification task in the agriculture field. The path boundary was determined with edge detection and the Hough transform, and it was compared to the actual path boundary. The average lateral error was approximately 11.4 cm, and the average angle error was approximately 8.9°. The proposed technique can perform as well as other approaches; however, it only needs low cost memory to execute the process unlike other deep learning-based approaches. It is possible that an autonomous farm robot can be easily developed with this proposed technique using a simple hardware configuration.

• Education of Primary School Mathematics
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• v.21 no.2
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• pp.111-130
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• 2018

In this study, I compared and analyzed the contents of Korean, Japanese, Singapore, American, and Finnish textbooks about fraction which is one of the important and difficult concepts in elementary school mathematics. This is aimed to get the implications for meaningful fractional teaching and learning by analyzing the advantages and disadvantages of the methods and time of introducing the concept because fraction has the diversity of the sub-concepts and the introducing methods or process. As a result of the analysis, the fraction was introduced as part-whole(area) in all five countries' textbooks, but the use of number line, conversion between improper fraction and mixed number, whether to deal with part-whole(set) model. Furthermore, there are differences in the methods in obtaining of the equivalent fraction and the order of arrangement in comparison of fraction. Through this analysis, we discussed the reconsideration of the introducing contexts of fractions, the use of number line when introducing fractions, and the problem of segmentation and classification of contents.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.2
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• pp.137-146
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• 1990

A series of images whose sized and resolutions differ by a constant factor are called an image pyramid. Because the images at high levels are small, large object can be detected on high levels of the pyramid at low cost, But in this way, the boundaries of objects are not accurately localized. Therefore the pyramid algorithms extracte the objects by segmentation the constructed image using bottom-up method and description it in an original resolution using inverse bottom-up method. In this paper, we can project an object down to the next lower level of the pyramid and apply to the boundary adjustment algorithm at that level to localize it more precisely. We repeat the process at successively lower levels. In this paper, we present a method of boundary adjustment using an image pyramid to obtain optimal boundary. The performance of the proposed algorithm is compared to those of the conventional method in term of subjective quality of object boundary.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.971-974
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• 2005

Science and technology-related societies in the interior of a country sum up to approximately 660, and are increasing yearly, due to the development of new research fields and segmentation of past studies. Such societies are contributed with latest academic research information, and the submitted studies go through an review process before publication. A majority of the societies employ the traditional off-line review method; various problems and issues occur in delay of submission, review, revision, and management of the numerous paper submitted and published. Therefore, this study suggests the design of, and implemented an on-line paper review system which processes on-line submission and review of paper, facilitates swift and review progress, and enables efficient control and management on general tasks and academic information through integrated administration of members and published works.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.339-346
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• 2003

In this paper, we propose a new method in which interpolation images are created by using a small number of axiai T2-weighted images instead of using many sectional images for 3D visualization of brain MR images. For image Interpolation, an important part of this process, we first segment a region of interest (ROI) that we wish to apply 3D reconstruction and extract the boundaries of segmented ROIs and MBR information. After the image size of interpolation layer is determined according to the changing rate of MBR size between top slice and bottom slice of segmented ROI, we find the corresponding pixels in segmented ROI images. Then we calculate a pixel's intensity of interpolation image by assigning to each pixel intensity weights detected by cube interpolation method. Finally, 3D reconstruction is accomplished by exploiting feature points and 3D voxels in the created interpolation images.

• Journal of Biosystems Engineering
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• v.29 no.1
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• pp.71-78
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• 2004

Real time and robust algorithm to extract the features of watermelon was developed from the remotely transmitted image of the watermelon. Features of the watermelon at the cultivation site such as size and shape including position are crucial to the successful tole-robotic operation and development of the cultivation data base. Algorithm was developed based on the concept of task sharing between the computer and the operator utilizing man-computer interface. Task sharing was performed based on the functional characteristics of human and computer. Identifying watermelon from the image transmitted from the cultivation site is very difficult because of the variable light condition and the complex image contents such as soil, mulching vinyl, straws on the ground, irregular leaves and stems. Utilizing operator's teaching through the touch screen mounted on the image monitor, the complex time consuming image processing process and instability of processing results in the watermelon identification has been avoided. Color and brightness characteristics were analyzed from the image area specified by the operator's teaching. Watermelon segmentation was performed using the brightness and color distribution of the specified imae processing area. Modified general Hough transform was developed to extract the shape, major and minor axes, and the position, of the watermelon. It took less than 100 msec of the image processing time, and was a lot faster than conventional approach. The proposed method showed the robustness and practicability in identifying watermelon from the wireless transmitted color image of the cultivation site.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.5
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• pp.628-638
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• 1999

In this paper, we presents a method of retrieving 24 bpp RGB images based on color-spatial features. For each image, it is subdivided into regions by using similarity of color after converting RGB color space to CIE L*u*v* color space that is perceptually uniform. Our segmentation algorithm constrains the size of region because a small region is discardable and a large region is difficult to extract spatial feature. For each region, averaging color and center of region are extracted to construct color-spatial features. During the image retrieval process, the color and spatial features of query are compared with those of the database images using our similarity measure to determine the set of candidate images to be retrieved. We implement a content-based color image retrieval system using the proposed method. The system is able to retrieve images by user graphic or example image query. Experimental results show that Recall/Precision is 0.80/0.84.