• KIPS Transactions on Software and Data Engineering
• /
• v.2 no.1
• /
• pp.27-34
• /
• 2013

Background subtraction is one of the key techniques for automatic video content analysis, especially in the tasks of visual detection and tracking of moving object. In this paper, we present a new sample-based technique for background extraction that provides background image as well as background model. To handle both high-frequency and low-frequency events at the same time, multiple interval background models are adopted. The main innovation concerns the use of a confidence factor to select the best model from the multiple interval background models. To our knowledge, it is the first time that a confidence factor is used for merging several background models in the field of background extraction. Experimental results revealed that our approach based on multiple interval sampling works well in complicated situations containing various speed moving objects with environmental changes.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.3
• /
• pp.271-274
• /
• 2006

This paper deals with a similarity decision method between the shape of hand-postures and their structures to improve performance of the vision-based hand-posture recognition system. Hand-posture recognition by vision sensors has difficulties since the human hand is an object with high degrees of freedom, and hence grabbed images present complex self-occlusion effects and, even for one hand-posture, various appearances according to viewing directions. Therefore many approaches limit the relative angle between cameras and hands or use multiple cameras. The former approach, however, restricts user's operation area. The latter requires additional considerations on the way of merging the results from each camera image to get the final recognition result. To recognize hand-postures, we use both of appearance and structural features and decide the similarity between the two types of features by learning.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.5
• /
• pp.573-580
• /
• 2005

In this paper, we propose an emotion recognition using static and dynamic facial images to effectively design human interface. The proposed method is constructed by HMM(Hidden Markov Model), PCA(Principal Component) and wavelet transform. Facial database consists of six basic human emotions including happiness, sadness, anger, surprise, fear and dislike which have been known as common emotions regardless of nation and culture. Emotion recognition in the static images is performed by using the discrete wavelet. Here, the feature vectors are extracted by using PCA. Emotion recognition in the dynamic images is performed by using the wavelet transform and PCA. And then, those are modeled by the HMM. Finally, we obtained better performance result from merging the recognition results for the static images and dynamic images.

• The Journal of Korean Academy of Prosthodontics
• /
• v.57 no.4
• /
• pp.425-431
• /
• 2019

This clinical case report describes the digital workflow that combines a face scan, cone beam computed tomography and an intraoral scan to visualize the outcome of prosthodontic treatment in the anterior region. This approach improves communication between clinic, laboratory and patients. A patient with healthy general condition came for a restorative treatment to treat post-traumatic central incisors of maxilla. A virtual patient replica was made by incorporating a face scan, cone beam computed tomography and an intraoral scan. Design mockup of definitive restorations was shown to the patient and modified according to the patient's desire. This digital workflow facilitates the fabrication of optimal esthetic restorations, and enhances the predictability of outcome of restorations.

• Journal of Platform Technology
• /
• v.9 no.4
• /
• pp.71-78
• /
• 2021

Self-driving vehicles are increasing as new alternatives to solving problems such as human safety, environment and aging. And such technology development has a great ripple effect on other industries. However, various problems are occurring. The number of casualties caused by self-driving is increasing. Although the collision of fixed obstacles is somewhat decreasing, on the contrary, the technology by active obstacles is still insignificant. Therefore, in this study, in order to solve the core problem of self-driving vehicles, we propose a method of extracting active obstacles on the road. First, a center scene is extracted from a continuous image. In addition, it was proposed to extract activity obstacles using activity size and activity repeatability information from objects included in the center scene. The center scene is calculated using region segmentation and merging. Based on these results, the size of the frequency for each pixel in the region was calculated and the size of the activity of the obstacle was calculated using information that frequently appears in activity. Compared to the results extracted directly by humans, the extraction accuracy was somewhat lower, but satisfactory results were obtained. Therefore, it is believed that the proposed method will contribute to solving the problems of self-driving and reducing human accidents.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.25 no.4
• /
• pp.49-62
• /
• 2022

Borehole Data is geotechnical information provided so that workers can safely perform construction at the field. It creates 3D data and supports viewing as a 3D image. Currently, all Korean companies that develop programs using 3D visualization use the MVS program developed by C Tech Development Corporation. However, the MVS program is a commercial program, and it is difficult to use MVS in 3D related programs developed by Korean Companies. In this paper, we propose to develop a program that can replace MVS to generate a 3D stratum model from clustered borehole information using Python's Gempy open-source. The 3D stratum model program can creates point data for each stratum and can creates a surface for each stratum through interpolation. Then, the 3D stratum model program is completed by merging the surfaces of each stratum. It was confirmed that there was no difference when a 3D model was created and compared with the MVS program and the proposed program from the borehole data of a Goyang area.

• Korean Journal of Remote Sensing
• /
• v.14 no.2
• /
• pp.175-195
• /
• 1998

Automatic lineament extraction algorithms had been developed by various researches for geological purpose using remotely sensed data. However, most of them are designed for a certain topographic model, for instance rugged mountainous region or flat basin. Most of common topographic characteristic in Korea is a mountainous region along with alluvial plain, and consequently it is difficult to apply previous algorithms directly to this area. A new algorithm of automatic lineament extraction from remotely sensed images is developed in this study specifically for geological applications. An algorithm, named as DSTA(Dynamic Segment Tracing Algorithm), is developed to produce binary image composed of linear component and non-linear component. The proposed algorithm effectively reduces the look direction bias associated with sun's azimuth angle and the noise in the low contrast region by utilizing a dynamic sub window. This algorithm can successfully accomodate lineaments in the alluvial plain as well as mountainous region. Two additional algorithms for estimating the individual lineament vector, named as ALEHHT(Automatic Lineament Extraction by Hierarchical Hough Transform) and ALEGHT(Automatic Lineament Extraction by Generalized Hough Transform) which are merging operation steps through the Hierarchical Hough transform and Generalized Hough transform respectively, are also developed to generate geological lineaments. The merging operation proposed in this study is consisted of three parameters: the angle between two lines($\delta$$\beta$), the perpendicular distance($(d_ij)$), and the distance between midpoints of lines(dn). The test result of the developed algorithm using Landsat TM image demonstrates that lineaments in alluvial plain as well as in rugged mountain is extremely well extracted. Even the lineaments parallel to sun's azimuth angle are also well detected by this approach. Further study is, however, required to accommodate the effect of quantization interval(droh) parameter in ALEGHT for optimization.

• The KIPS Transactions:PartB
• /
• v.16B no.2
• /
• pp.131-140
• /
• 2009

This paper presents a new algorithm to the segmentation of the FISH images. First, for segmentation of the cell nuclei from background, a threshold is estimated by using the gaussian mixture model and maximizing the likelihood function of gray value of cell images. After nuclei segmentation, overlapped nuclei and isolated nuclei need to be classified for exact nuclei analysis. For nuclei classification, this paper extracted the morphological features of the nuclei such as compactness, smoothness and moments from training data. Three probability density functions are generated from these features and they are applied to the proposed Bayesian networks as evidences. After nuclei classification, segmenting of overlapped nuclei into isolated nuclei is necessary. This paper first performs intensity gradient transform and watershed algorithm to segment overlapped nuclei. Then proposed stepwise merging strategy is applied to merge several fragments in major nucleus. The experimental results using FISH images show that our system can indeed improve segmentation performance compared to previous researches, since we performed nuclei classification before separating overlapped nuclei.

• The KIPS Transactions:PartB
• /
• v.16B no.1
• /
• pp.7-16
• /
• 2009

Some clustering algorithms have a problem that an image is over-segmented since both the spatial information between the segmented regions is not considered and the number of the clusters is defined in advance. Therefore, they are difficult to be applied to the applicable fields. This paper proposes the new post-processing methods, a reclassification of the inhomogeneous clusters and a region merging using Baysian algorithm, that improve the segmentation results of the clustering algorithms. The inhomogeneous cluster is firstly selected based on variance and between-class distance and it is then reclassified into the other clusters in the reclassification step. This reclassification is repeated until the optimal number determined by the minimum average within-class distance. And the similar regions are merged using Baysian algorithm based on Kullbeck-Leibler distance between the adjacent regions. So we can effectively solve the over-segmentation problem and the result can be applied to the applicable fields. Finally, we design a classification system for the segmented regions to validate the proposed method. The segmented regions are classified by SVM(Support Vector Machine) using the principal colors and the texture information of the segmented regions. In experiment, the proposed method showed the validity for various real-images and was effectively applied to the designed classification system.

• Asia Marketing Journal
• /
• v.12 no.4
• /
• pp.183-201
• /
• 2011

In case of Aju capital, it adopted a strategy to use a single brand not two separate brands after M&A was completed. In order to implement this strategy, it has endeavored to effectively process the work of shifting existing marketing infrastructure of DAEWOO capital, the mergee, spending enough transition time for the brand migration. In the process of merging, Aju capital picked the strategy to use the brand of mergee first, which is the Daewoo Capital brand, and then took a transition time for a while to converge to the single brand of Aju capital. Putting another way, even if the M&A deal was completed back in 2005, it maximized the effect of launching its final brand "Aju capital" by capitalizing on the positive image of "Daewoo" during the transition time and changing its name just in the right moment. In a bid to implement this strategy successfully, it established a cautious but sophisticated brand migration strategy. 1) "Brand bridge" strategy through reinforcing brand power of "Naegeron", which is an individual product brand of Daewoo Capital 2) Establishing a good brand image through reinforcing customer satisfaction 3) It implemented and completed its brand transition initiative by going through the step of Aju Capital brand unification (from Sept 09 to present) Currently, the sales unit of Aju Capital is realizing quality growth through specialization. It's strategy is to construct a systematic sales portfolio in terms of both quality and quantity through product-by-product specialization where the existing practice was selling a variety of products in a single branch. Back in 2009, it opened a branch that specialize in imported cars and expanded its used car business to 6 specialized locations. Besides, the specialized locations for personal loan named "Naegeron" was expanded from 3 to 11 locations. Recently, it is expected that it will inject vigor to retail and corporate financing business alongside with its core business, which is auto financing.