• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.128-137
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• 2011

The purpose of the FAPIS(Forest Aerial Photograph Interpretation System) development is to increase accuracy and efficiency of the digital forest cover type mapping for improving conventional analog-based mapping procedures by optimizing work-flow and mapping technology. The database models including digital forest cover type map, aerial photograph, and topographic map were designed for use in this system construction. The interface configured concisely to connect with functions such as search engine, display control, conversion to stereo interpretation mode, modification tools, automation of print layout and database models. It is expected that the standardization methodology based on this system can be applied and extended in making all kinds of digital thematic maps, providing decision-making and information of forest resources.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.42-57
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• 2022

This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.321-326
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• 2021

Blockchain is increasing in value as a platform for safe transmission of capital transactions or secure data. In addition, blockchain has the potential as a new platform that can safely store large amounts of data such as videos, music, and photos, and safely manage transaction details and service usage specifications. Since it is not possible to store large-capacity media data in a block, research on the performance of storing sound source information in a block and retrieving the stored sound source data by using the distributed storage system (IPFS) and the hash information of the sound source signature data was conducted. In this paper, we propose a sound source signature indexing method using a bloom filter that can improve the search speed suggested by previous studies. As a result of the experiment, it was confirmed that improved search performance (O(1)) than the existing search performance (O(n)) can be achieved.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.97-103
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• 2018

In oriental paintings, there is Luo-kuan that expressed in a single picture by compressing the artist's information. Such Luo-kuan includes various information such as the title of the work or the name of the artist. Therefore, information about Luo-kuan is considered important to those who collect or enjoy oriental paintings. However, most of the letters in the Luo-kuan are difficult kanji, kanzai, or various shapes, so it is difficult for the ordinary people to interpret. In this paper, we developed an Luo-kuan search application to easily check the information of the Luo-kuan. The application uses a search algorithm that analyzes the captured Luo-kuan image and sends it to the server to output information about the Luo-kuan candidates that are most similar to the Luo-kuan images taken from the database in the server. We also compared and analyzed the accuracy of the algorithm based on 170 Luo-kuan data in order to find out the ranking of the Luo-kuan that matched the Luo-kuan among the candidates. Accuracy Analysis Experimental Results The accuracy of the search algorithm of this application is confirmed to be about 90%, and it is anticipated that it will be possible to develop a platform to automatically analyze and search images in a big data environment by supplementing the optimizing algorithm and multi-threading algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.9-16
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• 2024

It is difficult to know the efficacy of pills if the pill bag or wrapper is lost after purchasing the pill. Many people do not classify the use of commercial pills when storing them after purchasing and taking them, so the inaccessibility of information on the side effects of pills leads to misuse of pills. Even with existing applications that search and provide information about pills, users have to select the details of the pills themselves. In this paper, we develope a pill recognition application by building a model that learns the formulation and colour of 22,000 photos of pills provided by a Pharmaceutical Information Institution to solve the above situation. We also develope a pill medication management function.

• Journal of Broadcast Engineering
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• v.19 no.3
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• pp.396-404
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• 2014

The field of searching clothing, which is very difficult due to the nature of the informal sector, has been in an effort to reduce the recognition error and computational complexity. However, there is no concrete examples of the whole progress of learning and recognizing for cloth, and the related technologies are still showing many limitations. In this paper, the whole process including identifying both the person and cloth in an image and analyzing both its color and texture pattern is specifically shown for classification. Especially, deformable search descriptor, LBPROT_35 is proposed for identifying the pattern of clothing. The proposed method is scale and rotation invariant, so we can obtain even higher detection rate even though the scale and angle of the image changes. In addition, the color classifier with the color space quantization is proposed not to loose color similarity. In simulation, we build database by training a total of 810 images from the clothing images on the internet, and test some of them. As a result, the proposed method shows a good performance as it has 94.4% matching rate while the former Dense-SIFT method has 63.9%.

• The Journal of the Convergence on Culture Technology
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• v.2 no.3
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• pp.35-40
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• 2016

This study is about developing an Android application that provides information on customized styling and the app was made to offer assistance in coordinating users' clothing. It keeps the record on clothing items users wore and uses it as coordination information, and prepares styling by referring to user-specific clothing management data. The photos can taken during shopping or can be taken from smart phone gallery, and the images searched through Daum OpenAPI can be saves in the app. Using the saved photos of items and clothes that were previously worn, the app provides styling recommendations.

• Korean journal of applied entomology
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• v.55 no.3
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• pp.205-214
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• 2016

A taxonomic study of Korean Berosus Leach is presented. Four species [Berosus (Berosus) japonicus Sharp, Berosus (Berosus) punctipennis Harold, Berosus (Enoplurus) lewisius Sharp, and Berosus (Enoplurus) spinosus (Steven)] in two subgenera are recognized, one of which [B. (E.) spinosus] is reported for the first time in Korea. We also found that B. (B.) puchellus MacLeay previously recorded in Korea was an incorrect identification of B. (E.) lewisius Sharp. Habitus and SEM photographs, key and diagnoses of the known species are provided.

• Korean journal of applied entomology
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• v.39 no.4
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• pp.227-237
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• 2000

Fourteen species of the genus Gonocephalum and one species of the genus Opatrum (Tenebrionidae, Opatrini) from Korea have been previously recorded. They are taxonomically reviewed based on many faunistic reports and research papers. We also examined many specimens including voucher materials of the previous studies. Among the recorded species, G. sabulosum is excluded because it was misidentified for the individual variation of Opatrum subaratum. We couldn’t find any Korean materials of four species (G. japanum, G. bilinearum, G. outreyi, G. malayanum), and used the materials determined from other countries. Key to 13 species of the genus Gonocephalum, illustrations of adults and male aedeagus are provided.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.12 no.1
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• pp.89-94
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• 1994

A number of the latest research projects focus on the development of real-time mapping system. Typically, these devices are used to capture land-related information in digital form from airplanes or cars. The purpose of this paper is to automatically extract the road information from the digital images obtained using the so-called "GPS-Van" which has been developed by Center for Mapping at The Ohio State University, and to propose the method for the effective storage and management of the digital data. The edges of a road can be extracted from the digital image and determined real-time 3-dimensional position by digital photogrammetry. Also, the three storage level which consists of raster data level, object-oriented data level, and vector data level in the data storage and Quadtree data structure for the effective compression and search in the data management was proposed in this paper.his paper.