• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.38 no.3
• /
• pp.237-246
• /
• 2001

A high speed context-free marker-controlled and minima imposition-free watershed transform is proposed for efficient multi-object detection and segmentation from a complex background. The context-free markers are extracted from a complex backgrounded multi-object image using a noise tolerant attention operator. These make marker-controlled watershed possible for the over-segmentation reduction without region merging. The proposed method presents a marker-constrained labeling that can speed up the segmentation of a marker-controlled watershed transform by eliminating the necessity of the minima imposition. Simulation results show that the proposed method can efficiently detects and segments multiple objects from a complex background while reducing over- segmentation and the computation time.

• Journal of Korea Multimedia Society
• /
• v.7 no.5
• /
• pp.648-657
• /
• 2004

A method of extracting central objects in color images without any prior-knowledge is proposed in this paper, which uses basically information of significant color distribution. A central object in an image is defined as a set of regions that lie around center of the image and have significant color distribution against the other surround (or background) regions. Significant colors in an image are first defined as the colors that are distributed more densely around center of the image than near borders. Then core object regions (CORs) are selected as the regions a lot of pixels of which have the significant colors. Finally, the adjacent regions to the CORs are iteratively merged if they are similar to the CORs but not to the background regions in color distribution. The merging result is accepted as the central object that may include differently color-characterized regions and/or two or more objects of interest. Usefulness of the significant colors in extracting the central object was verified through experiments on several kinds of test images. We expect that central objects shall be used usefully in image retrieval applications.

• Korean Journal of Remote Sensing
• /
• v.19 no.2
• /
• pp.135-147
• /
• 2003

This study used the multistage hierarchical clustering image classification to analyze the satellite images for the land-cover types of an area in the Korean peninsula. The multistage algorithm consists of two stages. The first stage performs region-growing segmentation by employing a hierarchical clustering procedure with the restriction that pixels in a cluster must be spatially contiguous, and finally the whole image space is segmented into sub-regions where adjacent regions have different physical properties. Without spatial constraints for merging, the second stage clusters the segments resulting from the previous stage. The image classification of hierarchical clustering, which merges step-by step two small groups into one large one based on the hierarchical structure of digital imagery, generates a hierarchical tree of the relation between the classified regions. The experimental results show that the hierarchical tree has the detailed information on the hierarchical structure of land-use and more detailed spectral information is required for the correct analysis of land-cover types.

• Korean Journal of Remote Sensing
• /
• v.22 no.6
• /
• pp.613-619
• /
• 2006

This study proposed an unsupervised image classification through the dendrogram of agglomerative clustering as a higher stage of image segmentation in image processing. The proposed algorithm is a hierarchical clustering which includes searching a set of MCSNP (Mutual Closest Spectral Neighbor Pairs) based on the data structures of RAG(Regional Adjacency Graph) defined on spectral space and Min-Heap. It also employes a multi-window system in spectral space to define the spectral adjacency. RAG is updated for the change due to merging using RNV (Regional Neighbor Vector). The proposed algorithm provides a dendrogram which is a graphical representation of data. The hierarchical relationship in clustering can be easily interpreted in the dendrogram. In this study, the proposed algorithm has been extensively evaluated using simulated images and applied to very large QuickBird imagery acquired over an area of Korean Peninsula. The results have shown it potentiality for the application of remotely-sensed imagery.

• 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 the Institute of Electronics Engineers of Korea SP
• /
• v.37 no.2
• /
• pp.50-59
• /
• 2000

In this paper, a new preprocessing method is proposed to speedup the watershed-based image segmentation In the proposed method, the gradient correction values of ramp edges are calculated from the positions and width of the ramp edges using Laplacian operator, and then, unlike the conventional method in which the monoscale or multi scale gradient image is directly used as a reference iImage, the reference image is obtained by adding the threshold value to each position of the ramp edges in the monoscale gradient image And the marker image is reconstructed on the reference image by erosion By preprocessing the image for the watershed transformation in such a manner, we can reduce the oversegmentations far more than those of applying the conventional morphological filter to the simple monoscale or multiscale gradient-based reference image Thus, we can reduce the total image segmentation time by reducing the time of postprocessing of region merging, which consumes most of the processing time In the watershed-based image segmentation, Experimental results indicate that the proposed method can speedup the total image segmentation about twice than those of the conventional methods, without the loss of ramp edges and principal edges around the dense-edge region.

• Korean Journal of Remote Sensing
• /
• v.29 no.4
• /
• pp.423-441
• /
• 2013

On 21 September 2010, one of Chuseok holidays in Korea, localized heavy rainfalls occurred over the midwestern region of the Korean peninsula. In this study MTSAT-2 infrared and water vapor channel imagery are examined to find out some features which are obvious in each stage of the life cycle of convective cell for this heavy rain event. Also the kinematic and thermodynamic features probably associated with them are investigated. The first clouds related with the Chuseok heavy rain are detected as low-level multicell cloud (brightness temperature: $-15{\sim}0^{\circ}C$) in the middle of the Yellow sea at 1630~1900 UTC on 20 Sept., which are probably associated with the convergence at 1000 hPa. Convective cells are initiated in the vicinity of Shantung peninsula at 1933 UTC 20, which have developed around the edge of the dark region in water vapor images. At two times of 0033 and 0433 UTC 21 the merging of two convective cells happens near midwestern coast of the peninsula and then they have developed rapidly. From 0430 to 1000 UTC 21, key features of convective cell include repeated formation of secondary cell, slow horizontal cloud motion, persistence of lower brightness temperature ($-75{\sim}-65^{\circ}C$), and relatively small cloud size (${\leq}-50^{\circ}C$) of about $30,000km^2$. Radar analysis showed that this heavy rain is featured by a narrow line-shaped rainband with locally heavy rainrate (${\geq}50$ mm/hr), which is located in the south-western edge of the convective cell. However there are no distinct features in the associated synoptic-scale dynamic forcing. After 1000 UTC 21 the convective cell grows up quickly in cloud size and then is dissipated. These satellite features may be employed for very short range forecast and nowcasting of mesoscale heavy rain system.

• 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.

• Journal of the Korean Regional Science Association
• /
• v.15 no.2
• /
• pp.131-153
• /
• 1999

Since 1980's there have been two trends that obviously developed in the would -- economics globalization and urban internationalization. China, with is reform and opening-up policy and rapid economic growth, keeps pace with these two trends. The term "International City" has no putative standard or definition. If we make an analogue of urban functional hierarchy in the world with a pyramid, the International Citiesa are the few elites on its top. The highest level international cities can be called "World City" or "Global City". In today's new international division of labor, they are diversified leading cities with control capacity on a world scale, like New York, London, and Tokyo. The secondary international cities are either diversified cities with influence and regulative functions on multinational scale or specialized cities on politics, economics, culture, or other aspects with worldwide impact. Judged by different criteria, there is no city that is qualified as International City with the exception of Hong Kong, which was returned to the P.R. of China in 1997. Nevertheless, Some favorable conditions for the development of the international city still exist in China. This country is already the sixth largest economic entity in the world, and the second largest economic entity in the world, and the second largest one if GNP estimated by ppp. Furthermore its import and export value make up for 40% of its GNP, indicating that China is repidly merging into global economy. In this 1, 2 billion-population country, the difference of economic levels between urban and rural, coastal and inland regions is so big that a few metropolises in the coastal region have the possibilities and potentials to develop into international cities regardless of rather low GNP per capita of the whole country. This article will focus on analysis from several perspectives, such as the proportion of foreign trade values in GDP, the proportion of imports and exports by foreign funded enterprises in total foreign trade value; distribution of the 500 largest foreign-funded enterprises; distribution of the 500 enterprises with largest import and export values; distrigbution of foreign computer and telecom companies with offices in China; the number of outward flights per week and the international tourists; the value of foreign capital used in cities and so on. From this analysis, it is predicted that Chinese international cities will surely emergy from the eastern coastal regions and they must be the core cities of metropolitan interlocking regions that have been formed or in the process of forming. Those international cities will arise from south to north in turn : Hong Kong-Guangzhu, Shanghai, Beijing-Tianjin, and perhaps the last one is Dalian-Shenyang. The other side of this issue is that there is a long way for the coming international cities in China except Hong Kong. At least China and these core cities must continually devote to (1) improve the regional composition of foreign capital sources. (2) improve the composition of export commodities. (3) improve the investment environment (including hard and soft environment) to attract more transnational corporations to settle. (4) deepen the reform of state-owned enterprises and establish Chinese own transnational corporations to enter the world market.ons to enter the world market.

• Korean Journal of Remote Sensing
• /
• v.32 no.6
• /
• pp.551-566
• /
• 2016

In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. The degradation results in noise and blurring which badly affect identification and extraction of useful information in image data. Especially, the degradation gives bad influence in the analysis of images collected over the scene with complicate surface structure such as urban area. This study proposes a multi-stage image restoration to improve the accuracy of detailed analysis for the images collected over the complicate scene. The proposed method assumes a Gaussian additive noise, Markov random field of spatial continuity, and blurring proportional to the distance between the pixels. Point-Jacobian Iteration Maximum A Posteriori (PJI-MAP) estimation is employed to restore a degraded image. The multi-stage process includes the image segmentation performing region merging after pixel-linking. A dissimilarity coefficient combining homogeneity and contrast is proposed for image segmentation. In this study, the proposed method was quantitatively evaluated using simulation data and was also applied to the two panchromatic images of super-high resolution: Dubaisat-2 data of 1m resolution from LA, USA and KOMPSAT3 data of 0.7 m resolution from Daejeon in the Korean peninsula. The experimental results imply that it can improve analytical accuracy in the application of remote sensing high resolution panchromatic imagery.