• Journal of KIISE:Software and Applications
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• v.30 no.5_6
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• pp.444-453
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• 2003

Recently, a great interest of bio-technology(BT) is concentrated and the image analysis technique for electrophoresis gels is highly requested to analyze genetic information or to look for some new bio-activation materials. For this purpose, the location and quantity of each band in a lane should be measured. In most of existing techniques, the approach of peak searching in a profile of a lane is used. But this peak is improper as the representative of a band, because its location does not correspond to that of the brightest pixel or the center of gravity. Also, it is improper to measure band quantity in most of these approaches because various enhancement processes are commonly applied to original images to extract peaks easily. In this paper, we adopt an approach to measure accumulated brightness as a band quantity in each band region, which Is extracted by not using any process of changing relative brightness, and the gravity center of the region is calculated as a band location. Actually, we first extract lanes with an entropy-based threshold calculated on a gel-image histogram. And then, three other methods are proposed and applied to extract bands. In the MER method, peaks and valleys are searched on a vertical search line by which each lane is bisected. And the minimum enclosing rectangle of each band is set between successive two valleys. On the other hand, in the RG-1 method, each band is extracted by using region growing with a peak as a seed, separating overlapped neighbor bands. In the RG-2 method, peaks and valleys are searched on two vertical lines by which each lane is trisected, and the left and right peaks nay be paired up if they seem to belong to the same band, and then each band region is grown up with a peak or both peaks if exist. To compare above three methods, we have measured the location and amount of bands. As a result, the average errors in band location of MER, RG-1, and RG-2 were 6%, 3%, and 1%, respectively, when the lane length is normalized to a unit value. And the average errors in band amount were 8%, 5%, and 2%, respectively, when the sum of band amount is normalized to a unit value. In conclusion, RG-2 was shown to be more reliable in the accuracy of measuring the location and amount of bands.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.3
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• pp.483-494
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• 2019

From the cosmopolitan superiority of the as the first world map completed in 1402 with surprisingly detailed images and contents on the Africa Continent it is reasonable to think that the Koreans in early fifteen century were already with highly up-to-date perspectives on the universe and world history and cultures. However, some 490 year later the first phytohydrographic plankton investigation in the neritic seas of Korea was performed by a Japanese company with sampling points covering from Tokyo Bay through Jeju neritic waters to Shanghai estuary, which was in turn preceded by the first oceanographic investigation other than the simple mapping Koreans seas by using two French sailboats. The first phytohydrographic plankton investigation in Korean seas were behind the world first oceanic plankton exploration, the German Plankton Expedition, by 25 years. Starting from the oceanographic investigation including phytohydrographic samplings in the whole Yellow Sea in 1915 the full-scale phytohydrographic plankton studies were tried in Korean seas which is well represented by the 1921 oceanographic investigation on the whole East Sea with 80 sampling stations. In 1932 two separate oceanographic investigations followed, one in the East Sea where 78 stations from Busan to southern Sakhalin Island were simultaneously visited by 50 research vessels for the physical, chemical, and biological oceanographic studies, and the other one in southern coast and western East Sea of Korea where ocean current observation as well as plankton sampling were made in 120 stations to understand the relationship between the ocean current and plankton distribution in the region. In 1933-1934 more intensified investigations on phytohydrography were carried out particularly in the East Sea as an integral part of the basic marine ecosystem studies for the Myeong-Tae (Alaska Pollock) resources estimation. Scientists' attitude for the marine investigation and research activities seemed to be almost unchanging even to the year 1943, which could be reflected by the fact that publication of the results from the investigations performed in 1945 were finally done in 1967 at Tokyo. Some 70 years later from the mid-twenty century we might be standing on the turning-point of "need to be prepared" for the new era of changing paradigm by reviewing, archiving, and analyzing the prior information big data from the previous ocean observation and biohydrographic investigations. At the same time each professional societies for the above mentioned sciences might trigger a continuous project to reorganize and update the records on related bibliography and its history every 30 years.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1332-1344
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• 2004

Upon development of information super-highway and multimedia-related technoiogies in recent years, more efficient technologies to transmit, store and retrieve the multimedia data are required. Among such technologies, firstly, it is common that the semantic-based image retrieval is annotated separately in order to give certain meanings to the image data and the low-level property information that include information about color, texture, and shape Despite the fact that the semantic-based information retrieval has been made by utilizing such vocabulary dictionary as the key words that given, however it brings about a problem that has not yet freed from the limit of the existing keyword-based text information retrieval. The second problem is that it reveals a decreased retrieval performance in the content-based image retrieval system, and is difficult to separate the object from the image that has complex background, and also is difficult to extract an area due to excessive division of those regions. Further, it is difficult to separate the objects from the image that possesses multiple objects in complex scene. To solve the problems, in this paper, I established a content-based retrieval system that can be processed in 5 different steps. The most critical process of those 5 steps is that among RGB images, the one that has the largest and the smallest background are to be extracted. Particularly. I propose the method that extracts the subject as well as the background by using an Image, which has the largest background. Also, to solve the second problem, I propose the method in which multiple objects are separated using RGB channel selection techniques having optimized the excessive division of area by utilizing Watermerge's threshold value with the object separation using the method of RGB channels separation. The tests proved that the methods proposed by me were superior to the existing methods in terms of retrieval performances insomuch as to replace those methods that developed for the purpose of retrieving those complex objects that used to be difficult to retrieve up until now.