• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2007.10a
• /
• pp.154-157
• /
• 2007

The austenite phase observed in low carbon HSLA steels is well known to be decomposed to various bainitic microstructures, such as granular bainite, acicular ferrite and bainitic ferrite during continuous cooling process. These bainitic microstructures have been usually identified by using either scanning electron microscope (SEM) or transmission electron microscope (TEM). However, SEM and TEM images do no exactly coincide, because of the quite different sample preparation method in SEM and TEM observations. These conventional analysis method is, thus, not suitable for characterization of the complex bainitic microstructure. In this study, focused ion beam (FIB) technique was applied to make site-specific TEM specimens and to identify the 3-dimensional grain morphologies of the bainitic microstructure. The morphological feature and grain boundary characteristics of each bainitic microstructure were exactly identified.

• Journal of the Society of Naval Architects of Korea
• /
• v.53 no.3
• /
• pp.180-187
• /
• 2016

As distinct from a slender body, the separation of the boundary layer on a bluff body give rise to complex wakes in which various kinds of vortices form, develop and interact with each other. In this paper, we investigate cavitation wake field behind wedge shaped two-dimensional fin models. Eight different models are tested at the Chungnam National University Cavitation Tunnel (CNU-CT). First, we measure wake cavity shapes and compare with numerical results, which shows the good agreement with each other. In addition, we demonstrate that wake flow characteristics of the control fin are clearly identified by the correlation analysis of high-speed camera images and pressure fluctuation measurements.

• Proceedings of the Membrane Society of Korea Conference
• /
• 1995.04a
• /
• pp.16-20
• /
• 1995

The spontaneous self-organization of amphiphilic molecules into complex aggregates was undoubtedly an important factor in the emergence of life on earth. We study the parameters governing the self-organization of a simple amphiphilic model system using electron cryomicroscopy of ice-embedded specimens in combination with extensive data analysis. Different stable helices can be generated reproducibly by changing the parameters controlling the molecular aggregation process. The repeating units of the helical aggregates in the micrographs can be found by multivariate statistical image analysis techniques, and these two-dimensional projection images suffice for calculating the three-dimensional density distribution of the fibers. We present a typical structure consisting of a narrow stack of compartmented bilayers twisted into a left-handed helix. Our new techniques directly elucidate the three-dimensional structure of helical assemblies, and can complement or replace diffraction-based approaches.

• Proceedings of the Korean Powder Metallurgy Institute Conference
• /
• 2006.09b
• /
• pp.1061-1062
• /
• 2006

This paper presents a new approach for analyzing the microstructure of $SiC_p$-reinforced aluminum matrix composites from digital images. Various samples of aluminum matrix composite were fabricated by hot pressing the powder mixtures with certain volume and size combinations of pure Al and SiC particles. Microstructures of the samples were analyzed by computer-based image processing methods. Since the conventional methods are not suitable for separating phases of such complex microstructures, some new algorithms have been developed for the improved recognition and characterization of the particles in the metal matrix composites.

• Smart Media Journal
• /
• v.1 no.4
• /
• pp.27-34
• /
• 2012

In this paper, a novel text binarization is presented that can deal with some complex conditions, such as shadows, non-uniform illumination due to highlight or object projection, and messy backgrounds. To locate the target text region, a focus line is assumed to pass through a text region. Next, connected component analysis and stroke width estimation based on location information of the focus line is used to locate the bounding box of the text region, and each box of connected components. A series of classifications are applied to identify whether each CC(Connected component) is text or non-text. Also, a modified K-means clustering method based on an HCL color space is applied to reduce the color dimension. A text binarization procedure based on location of text component and seed color pixel is then used to generate the final result.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.14 no.3
• /
• pp.162-170
• /
• 2014

Appearance-based subspace models such as eigenfaces have been widely recognized as one of the most successful approaches to face recognition and tracking. The success of eigenfaces mainly has its origins in the benefits offered by principal component analysis (PCA), the representational power of the underlying generative process for high-dimensional noisy facial image data. The sparse extension of PCA (SPCA) has recently received significant attention in the research community. SPCA functions by imposing sparseness constraints on the eigenvectors, a technique that has been shown to yield more robust solutions in many applications. However, when SPCA is applied to facial images, the time and space complexity of PCA learning becomes a critical issue (e.g., real-time tracking). In this paper, we propose a very fast and scalable greedy forward selection algorithm for SPCA. Unlike a recent semidefinite program-relaxation method that suffers from complex optimization, our approach can process several thousands of data dimensions in reasonable time with little accuracy loss. The effectiveness of our proposed method was demonstrated on real-world face recognition and tracking datasets.

• Bulletin of the Korean Chemical Society
• /
• v.31 no.4
• /
• pp.1004-1013
• /
• 2010

Three-dimensional superstructures of unique self-assemblies generated by exploring the conformational flexibility of various dipyrromethenes through creation of hydrogen-bonds with metal-halide anions are reported and the conformational diversity is thoroughly described in the solid and solution states by X-ray diffraction analysis and variable temperature NMR spectroscopy. The tetrahedral or octahedral structures of their precursors, various metal-dipyrromethene complexes, are also reported, based on the crystallographic data. STM images of the self-assemblies observed on graphite surfaces present interesting arrangements and appear as tubular bunches.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.8
• /
• pp.640-646
• /
• 2003

We presents an edge-based point correlation algorithm for fast and stable visual inspection system. Conventional algorithms based on NGC(normalized gray-level correlation) have to overcome some difficulties in applying automated inspection systems to real factory environment. First of all, NGC algorithms involve highly complex computation and thus require high performance hardware for realtime process. In addition, lighting condition in realistic factory environments is not stable and therefore intensity variation from uncontrolled lights gives many troubles for applying NGC directly as pattern matching algorithm. We propose an algorithm to solve these problems, using thinned and binarized edge data, which are obtained from the original image. A point correlation algorithm with the thinned edges is introduced with image pyramid technique to reduce the computational complexity. Matching edges instead of using original gray-level image pixels overcomes problems in NGC method and pyramid of edges also provides fast and stable processing. All proposed methods are proved by the experiments using real images.

• Proceedings of the IEEK Conference
• /
• 2000.07b
• /
• pp.906-909
• /
• 2000

Conventional caption extraction methods use the difference between frames or color segmentation methods from the whole image. Because these methods depend heavily on heuristics, we should have a priori knowledge of the captions to be extracted. Also they are difficult to implement. In this paper, we propose a method that uses little heuristics and simplified algorithm. We use topographical features of characters to extract the character points and use KMST(Kruskal minimum spanning tree) to extract the candidate regions for captions. Character regions are determined by testing several conditions and verifying those candidate regions. Experimental results show that the candidate region extraction rate is 100%, and the character region extraction rate is 98.2%. And then we can see the results that caption area in complex images is well extracted.

• Proceedings of the IEEK Conference
• /
• 2007.07a
• /
• pp.299-300
• /
• 2007

Along with the development of imaging sensors, hyperspectral imaging technology is growing rapidly and contributing to many fields of science nowadays. However, the bulky size and complex structure make it difficult to be processed. Focused on in this paper is the clustering utility, implemented in HYVEW, a program involving tools and functions to manipulate with hyperspectral images. The clustering process aims to partition the surface of the imaged area into subregions by grouping the spectra subject to the similarity of spectra.