• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.431-434
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• 2003

In this paper, we propose an efficient method not only f3r producing accurate region segmentation, solving the over-segmentation problem of watershed algorithm but also f3r reducing post-processing time by reducing computation loads. Through this proposed method, region segmentation of neighboring objects and discrimination of similar intensities were effectively obtained. Input image of watershed algorithm has used the derivative-based detectors such as Sobel and Canny. But proposed method uses the pixels-similarity-based detector, that is, SUSAN. By adopting this proposed method, we can reduce the noise problem and solve the problem of over-segmentation and not lose the edge information of objects. We also propose Zero-Crossing SUSAN. With Zero-Crossing SUSAN, the edge localization, times and computation loads can be improved over those obtained from existing SUSAN

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.46 no.2
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• pp.103-114
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• 2010

For an effective management of fisheries resources, we need fisheries informations necessary for the establishment of reasonable fishing effort and TAC distribution. To study the present state of by-catch and discard of gill-net fishery in the East Sea, we carried out fishing research using trammel nets in the coastal sea of Susan-port (Yangyang), Jangho-port (Samcheok) and Hupo-port (Uljin). As a result, a total of catch of Susan was 259,172g and that of Hopo was 577,638g. Thus Catch of Susan was 1.49 times more than that of Hupo considering the number of used fishing gear. And catch of Janho was 7.4 times more than that of Susan considering the number of experiment. Two methods of by-catch analysis in this study were used, one method is standardizing of listed species catching possible in fishing license, another method is regarding catch species under 1% of total catch as by-catch. As a result of by-catch analysis of two method, by-catch rate of Susan was 6.55% and 5.87% respectively, that of Hupo was 44.70% and 5.24% and that of Jangho was 0.96% and 2.31%. Discard rate of fish in Susan, Hupo and Jangho were 1.59%, 3.42%, 2.23% respectively.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.220-223
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• 2004

Automatic image registration is an essential element of remote sensing because remote sensing system generates enormous amount of data, which are multiple observations of the same features at different times and by different sensor. The general process of automatic image registration includes three steps: 1) The extraction of features to be used in the matching process, 2) the feature matching strategy and accurate matching process, 3) the resampling of the data based on the correspondence computed from matched feature. For step 2) and 3), we have developed an algorithms for automated registration of satellite images with RANSAC(Random Sample Consensus) in success. However, for step 1), There still remains human operation to generate GCP Chips, which is time consuming, laborious and expensive process. The main idea of this research is that we are able to automatically generate GCP chips with comer detection algorithms without GPS survey and human interventions if we have systematic corrected satellite image within adaptable positional accuracy. In this research, we use SUSAN(Smallest Univalue Segment Assimilating Nucleus) algorithm in order to detect the comer. SUSAN algorithm is known as the best robust algorithms for comer detection in the field of compute vision. However, there are so many comers in high-resolution images so that we need to reduce the comer points from SUSAN algorithms to overcome redundancy. In experiment, we automatically generate GCP chips from IKONOS images with geo level using SUSAN algorithms. Then we extract reference coordinate from IKONOS images and DEM data and filter the comer points using texture analysis. At last, we apply automatically collected GCP chips by proposed method and the GCP by operator to in-house automatic precision correction algorithms. The compared result will be presented to show the GCP quality.

• Journal of Surface Science and Engineering
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• v.40 no.1
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• pp.11-15
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• 2007

Stable metallic Cu/Zn nanoparticles were prepared in the base oil phase by hydrothermal method. The physical properties, such as crystal structure, crystallite size and crystallinity according to synthesis conditions have been investigated by XRD, FT-IR and TEM. In addition, 4-ball test has been performed in order to investigate the frictional wear properties of prepared nanosized Cu/Zn particles. The peaks of the X-ray diffraction pattern indicate that the particle size was very small and crystallinity of Cu/Zn particles was good. The micrographs of TEM showed that nanosized Cu/Zn particles possessed a spherical morphology with a narrow size distribution. The crystallite size of the Cu/Zn particles synthesized in base oils was 23-30 nm. It was found that the antiwear capacity increases with increasing Cu/Zn concentration. When the concentration of Cu/Zn was 5.0 wt%, the wear scar diameters was 0.38 mm.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.580-585
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• 2009

This paper introduces GP(Genetic Programming) based corner detectors for an image processing. Various empirical algorithms have been studied to improve computational speed and accuracy including typical approaches, such as Harris and SUSAN. The these techniques are highly efficient, because properties of corner points are inspected and reflected into the algorithms. However these approaches are limited in discovering an innovative algorithm. In this study, we try to discover a more efficient technique by creating corner detector automatically using evolution of GP. The proposed method is compared to the existing corner detectors for test images.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.466-469
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• 2002

Burr is a projected part of finished workpiece. It is unavoidable and undesirable by-product of most metal cutting or shearing process. Also, it must be removed to improve the fit of machined parts, safety of workers, and the effectiveness of finishing operation. But deburring process is one of manufacturing processes that have net been successfully automated, so deburring automation is strongly needed. This paper focused on developing a basic algorithm to find edge of workpiece and match two different image data for deburring automation which includes automatic recognition of parts, generation of deburring tool paths and edge/corner finding ability by analyzing the DXF drawing file which contains information of part geometry. As an algorithm for corner finding, SUSAN method was chosen. It makes good performance in finding edge and corner in suitable time. And this paper suggested a simple algorithm to find matching point between CCD image and drawing file.

• The Research Journal of the Costume Culture
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• v.24 no.3
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• pp.349-357
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• 2016

As a solemn and serious uniform, military uniform can be differentiated easily from any other clothing in the aspects of color, material and style. Inspired by military uniform, fashion designers have been applying military uniform elements into modern fashion design in recent years, which helps to bring military uniform from the trench onto international fashion runway. The primary method of this research is theory analysis method and exampling study method. Based on the collected materials of modern military uniform, this paper takes the fashion and cultural study theory of the famous American scholar Susan B. Kaiser as the leading theory to analyze four subject positions embodied in military uniform, including nation, rank, gender and time and space. By analyzing the subject positions embodied in military uniform, it shows the rich cultural connotation of military uniform and the function of various small details. Meanwhile, by giving specific examples, this paper explores the influences of military uniform on modern fashion design in respect to color, style, material, pattern and accessory. Through the conduct of this research, it comes to the conclusion that military uniform also has the characteristics and properties described in the fashion and cultural theory of Susan B. Kaiser, in addition, designers can be inspired by every specific object around them, which shows the talents of designers.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.6
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• pp.128-135
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• 2002

Burr is a projected part of finished workpiece. It is unavoidable and undesirable by-product of most metal cutting or shearing process. Also, it must be removed to improve the fit of machined parts, safety of workers, and the effectiveness of finishing operation. But deburring process Is one of manufacturing processes that have not been successfully automated, so deburring automation is strongly needed. This paper focused on developing a basic algorithm to find edge of workpiece and match two different image data for deburring automation which includes automatic recognition of parts, generation of deburring tool paths and edge/comer finding ability by analyzing the DXF drawing file which contains information of part geometry. As an algorithm fur corner finding, SUSAN method was chosen. It makes good performance in finding edge and corner in suitable time. And this paper suggested a simple algorithm to find matching point between CCD image and drawing file.

• Journal of Korean Society of Rural Planning
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• v.27 no.4
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• pp.13-24
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• 2021

This study used big data to analyze visitors' experiences in Fishing Experience Recreation Village. Through the portal site posting data for the past six years, the experience of visiting Fishing Experience Villages in Baekmi and Susan was analyzed. The analysis method used Text mining and Social Network Analysis which are Big data analysis techniques. Data was collected using Textom, and experience keywords were extracted by analyzing the frequency and importance of experience texts. Afterwards, the characteristics of the experience of visiting the Fishing Experience Village were identified through the analysis of the interaction between the experience keywords using 'U cinet 6.0' and 'NetDraw'. First, through TF and TF-IDF values, keywords such as "Gungpyeong Port", "Susan Port", and "Yacht Marina" that refer to the name of the port and the port facilities appeared at the top. This is interpreted as the name of the port has the greatest impact on the recognition of the Fishing Experience Villages, and visitors showed a lot of interest in the port facilities. Second, focusing on the unique elements of port facilities and fishing villages such as "mud flat experience", "fishing village experience", "Gungpyeong port", "Susan port", "yacht marina", and "beach" through the values of degree, closeness, and betweenness centrality interpreted as having an interaction with various experiences. Third, through the CONCOR analysis, it was confirmed that the visitor's experience was focused on the dynamic behavior, the experience program had the greatest influence on the experience of the visitor, and that the experience of the static and the dynamic behavior was relatively balanced. In conclusion, the experience of visitors in the Fishing Experience Villages is most affected by the environment of the fishing village such as the tidal flats and the coast and the fishing village experience program conducted at the fishing port facilities. In particular, it was found that fishing port facilities such as ports and marinas had a high influence on the awareness of the Fishing Experience Villages. Therefore, it is important to actively utilize the scenery and environment unique to fishing villages in order to revitalize the Fishing Experience Villages experience and improve the quality of the visitor experience. This study is significant in that it studied visitors' experiences in fishing village recreation villages using big data and derived the connection between fishing village and fishing village infrastructure in fishing village experience tourism.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.265-272
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• 2005

In this paper, we propose a technique which is speedily searching for correspondent points of two images using Voronoi-Distance, as an image registration method for feature based image mosaics. It extracts feature points in two images by the SUSAN corner detector, and then create not only the Voronoi Surface which has distance information among the feature points in the base image using a priority based Voronoi distance algorithm but also select the model area which has the maximum variance value of coordinates of the feature points in the model image. We propose a method for searching for the correspondent points in the Voronoi surface of the base image overlapped with the model area by use of the partitive search algorithm using queues. The feature of the method is that we can rapidly search for the correspondent points between adjacent images using the new Voronoi distance algorithm which has $O(width{\times}height{\times}logN)$ time complexity and the the partitive search algerian using queues which reduces the search range by a fourth at a time.