• Korean Journal of Computational Design and Engineering
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• v.6 no.4
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• pp.263-270
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• 2001

In stamping-die manufacturing, the first step is to build die patterns for lost wax casting process. A recent industry trend is to manufacture the die pattern using 3-axis NC machining. This study identifies technical considerations of the pattern machining caused by the characteristics of Styrofoam material, and proposes technical methods related to establishing a process plan and generating tool paths for optimizing the pattern machining. In this paper, the process plan includes the fellowing three items: 1) deter-mining a global machining sequence-a sequence of profile, top, bottom machining and two set-ups, 2) extracting machining features from a pattern model and merging them, and 3) determining a machining sequence of machining features. To each machining feature, this study determines the machining start point, generates the approach tool path, and proposes a tool path linking method fur reducing the distance of the cutter rapid motion. Finally, a smooth tool path generation and an automatic feedrate adjustment (AFA) method are introduced far raising the machining efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4557-4572
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• 2020

The Alaska competition provides an opportunity to study the practical problems of real-world steganalysis. Participants are required to solve steganalysis involving various embedding schemes, inconsistency JPEG Quality Factor and various processing pipelines. In this paper, we propose a method to ensemble multiple deep learning steganalyzers. We select SRNet and RESDET as our base models. Then we design a three-layers model ensemble network to fuse these base models and output the final prediction. By separating the three colors channels for base model training and feature replacement strategy instead of simply merging features, the performance of the model ensemble is greatly improved. The proposed method won second place in the Alaska 1 competition in the end.

• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.695-700
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• 2021

The Faster RCNN-based shellfish recognition algorithm is introduced for shellfish recognition studies that currently do not have any deep learning-based algorithms in a practical setting. The original feature extraction module is replaced by DenseNet, which fuses multi-level feature data and optimises the NMS algorithm, network depth and merging method; overcoming the omission of shellfish overlap, multiple shellfish and insufficient light, effectively solving the problem of low shellfish classification accuracy. In the complexifier test environment, the test accuracy was improved by nearly 4%. Higher testing accuracy was achieved compared to the original testing algorithm. This provides favourable technical support for future applications of the improved Faster RCNN approach to seafood quality classification.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.44.2-44.2
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• 2013

The local environmental effects on the active galactic nucleus(AGN) activity has been studied by many authors, but there is still controversy. We performed statistical analysis for nearby(0.01 < z < 0.05) volume limited(Mr < -19) sample via visual inspection based on Sloan Digital Sky Survey Data Release7. We visually inspect around 50,000 galaxy images to find peculiar objects which show not only ongoing merging features and tidal features, but also post merging features like shell or ring structures. We found that the frequency of AGN host galaxies is at least 2 times higher among peculiar galaxies than non-peculiar galaxies, and this trend is still visible when galaxy properties such as color or stellar mass are fixed. Furthermore, L[OIII] of peculiar galaxies is found to be more increased than those of normal galaxies. The majority of the most luminous AGN hosts show peculiar feature, which indicates that the luminous AGN galaxies may be the result of the local environmental effects. In addition, the enhancement of L[OIII] in peculiar galaxies is more significant for bluer galaxies, which implies that AGN activity is enhanced effectively when gas is available. In order to ensure our results, we also checked it for a smaller subsample with 2 magnitude deeper monochromatic images provided by SDSS Stripe82 database, and found consistent results. Overall, the results of this study tell us that the local environment of galaxies affects the frequency as well as the strength of AGN activity.

• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.29.4-30
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• 2009

Extra-tidal feature of the globular clusters such as tidal tails and halos can be a crucial evidence of the merging scenario of the Galaxy formation in the dynamical point of view. To search for such an extra-tidal feature of globular clusters located in the Galactic bulge(RGC<3kpc), we obtained wide-field near-infrared JHKs images of 6 metal-poor ([Fe/H]<-1.0) clusters and 3 metal-rich ([Fe/H]>-1.0) clusters. Observations were carried out using IRSF 1.4m telescope and SIRIUS near-infrared camera, during 2006~2007. The obtained images have a total maximum field-of-view of ~ $21'\times 21'$. To select clusters' member stars and minimize the field star contaminations, we applied CMD masking algorithm. Smoothed surface density contour maps with selected stars for each cluster show overdensity features around the tidal radius and beyond. Also, radial surface density profiles within the tidal radius of the clusters show an overdensity feature as a change of slope of the radial profile. The results add further observational constraints of the formation of the Galactic bulge.

• Journal of Korea Multimedia Society
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• v.5 no.4
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• pp.415-425
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• 2002

In this paper, we present a content-based image retrieval method which is based on the feature extraction in the wavelet transform domain. In order to overcome the drawbacks of the feature vector making up methods which use the global wavelet coefficients in subbands, we utilize the energy value of wavelet coefficients, and the shape-based retrieval of objects is processed by moment which is invariant in translation, scaling, rotation of the objects The proposed methods reduce feature vector size, and make progress performance of classification retrieval which provides fast retrievals times. To offer the abilities of region-based image retrieval, we discussed the image segmentation method which can reduce the effect of an irregular light sources. The image segmentation method uses a region-merging, and candidate regions which are merged were selected by the energy values of high frequency bands in discrete wavelet transform. The region-based image retrieval is executed by using the segmented region information, and the images are retrieved by a color, texture, shape feature vector.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.6
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• pp.1449-1457
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• 2007

A panorama image is constructed by merging several overlapped images to a big one. There are two kinds of methods, feature based and direct method, in the construction. Feature based one has a merit of processing speed faster than direct one. But, it is difficult to be implemented under slower processing environments such as mobile device. This paper proposed high speed construction method of a panorama image. The algorithm extremely improved matching speed by reducing the number of matching parameters using scene shot guider, and additionally adapted local matching technique to reduce matching error caused by the fewer matching parameters. In the experiments, it was shown that the proposed method required about 0.078 second in processing time, about 17 times shorter than the feature based one, for 24-bit color images of $320{\times}240$ size.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.1
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• pp.37-44
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• 2003

This study is focused on development of generalization processing for 1/25,000 digital mapping using l/5,000 digital map. The generalization processing for digital map included in spatial and attribute information consists of 3 steps. The first, elimination of layer which is not included in 1/25,000 feature code. The second, classification of 8 feature codes. The third, merging of spatial and attribute information. Therefore using generalization workflow developed in this project, automatic generalization system will develope optimal in the future and also contribute product to small scale digital map and thematic map.

• Speech Sciences
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• v.11 no.2
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• pp.193-210
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• 2004

In this paper, we develop a real time lip-synch system that activates 2-D avatar's lip motion in synch with an incoming speech utterance. To realize the 'real time' operation of the system, we contain the processing time by invoking merge and split procedures performing coarse-to-fine phoneme classification. At each stage of phoneme classification, we apply the support vector machine (SVM) to reduce the computational load while retraining the desired accuracy. The coarse-to-fine phoneme classification is accomplished via two stages of feature extraction: first, each speech frame is acoustically analyzed for 3 classes of lip opening using Mel Frequency Cepstral Coefficients (MFCC) as a feature; secondly, each frame is further refined in classification for detailed lip shape using formant information. We implemented the system with 2-D lip animation that shows the effectiveness of the proposed two-stage procedure in accomplishing a real-time lip-synch task. It was observed that the method of using phoneme merging and SVM achieved about twice faster speed in recognition than the method employing the Hidden Markov Model (HMM). A typical latency time per a single frame observed for our method was in the order of 18.22 milliseconds while an HMM method applied under identical conditions resulted about 30.67 milliseconds.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8B
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• pp.1391-1399
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• 2000

In this paper, we discussed the region-based image retrieval method using image segmentation. We proposed a segmentation method which can reduce the effect of a irregular light sources. The image segmentation method uses a region-merging, and candidate regions which are merged were selected by the energy values of high frequency bands in discrete wavelet transform. The content-based image retrieval is executed by using the segmented region information, and the images are retrieved by a color, texture, shape feature vector. The similarity measure between regions is processed by the Euclidean distance of the feature vectors. The simulation results shows that the proposed method is reasonable.