• KIPS Transactions on Software and Data Engineering
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• v.8 no.10
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• pp.391-396
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• 2019

Researches for image processing have been actively progress due to the development of various hardware. For example, in order to prevent various types of crime by a vehicle, there is a method of detecting the location of a criminal vehicle using the existing CCTV in real time. However, certain types of systems and high-performance system requirements make it difficult to apply to existing equipment. In this paper proposes a search algorithm that construct a file database of Korean standard license plate information so that specific vehicles can be quickly searched using existing equipment. In order to evaluate the performance of the file database and the search algorithm proposed in this paper, we set up the search targets at various locations and the results showed that the search algorithm could always check the information by searching the vehicle within a certain time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.11
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• pp.870-878
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• 2013

The objective of this paper is to develop mobile-based PACS(Picture Archiving Communication System: mPACS) for diagnostic medical image service available via Android-based mobile smartphone. The proposed mPACS provides an integrated platform for mobile application of diagnostic medical images stored in hospital PACS, and allows the smartphone to store, retrieve, manipulate and transfer the diagnostic medical images. Then, the mPACS platform includes the following features for use in the Android framework (i. e., diagnostic medical image processing) : transfer protocols between PACS, mPACS and smartphone, image format converter, JPEG and JPEG2000 coders, text and avatar search, and etc. This mPACS is shown to be useful and effective in providing a solution for mobile-based diagnostic medical image service.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.926-930
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• 2006

Current image retrieval techniques have shortcomings that make it difficult to search for images based on a semantic understanding of what the image is about. Since an image is normally associated with multiple contexts (e.g. when and where a picture was taken,) the knowledge of these contexts can enhance the quantity of semantic understanding of an image. In this paper, we present a context-aware image retrieval system, which uses the context information to infer a kind of metadata for the captured images as well as images in different collections and databases. Experimental results show that using these kinds of information can not only significantly increase the retrieval accuracy in conventional content-based image retrieval systems but decrease the problems arise by manual annotation in text-based image retrieval systems as well.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.158-165
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• 2018

Since a large amount of multimedia image has dramatically increased, it is important to search semantically relevant image. Thus, several semantic image annotation methods using RDF(Resource Description Framework) model in mobile environment are introduced. Earlier studies on annotating image semantically focused on both the image tag and the context-aware information such as temporal and spatial data. However, in order to fully express their semantics of image, we need more annotations which are described in RDF model. In this paper, we propose an annotation method inferencing with RDFS entailment rules and user defined rules. Our approach implemented in Moment system shows that it can more fully represent the semantics of image with more annotation triples.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.2
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• pp.11-22
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• 1992

Up to now, most researches on production automation have concentrated on local automation, e. g. CAD, CAM, robotics, etc. However, to achieve total automation it is required to link each local modules such as CAD, CAM into a unified and integrated system. One such missing link is between CAD and computer vision system. This thesis is an attempt to link the gap between CAD and computer vision system. In this paper, we propose algorithms that carry out edge detection, thinning and pruning from the image data of manufactured parts, which are obtained from video camera and then transmitted to computer. We also propose a feature extraction and surface determination algorithm which extract informations from the image data. The informations are compatible to IGES CAD data. In addition, we suggest a methodology to reduce search efforts for CAD data bases. The methodology is based on graph submatching algorithm in GEFG(Generalized Edge Face Graph) representation for each part.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.35-40
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• 2019

In this paper, we design and implement a partial denoising boundary matching system using indexing techniques. Converting boundary images to time-series makes it feasible to perform a fast search using indexes even on a very large image database. Thus, using this converting method we develop a client-server system based on the previous partial denoising research in the GUI(graphical user interface) environment. The client first converts a query image given by a user to a time-series and sends denoising parameters and the tolerance with this time-series to the server. The server identifies similar images from the index by evaluating a range query, which is constructed using inputs given from the client and sends the resulting images to the client. Experimental results show that our system provides many intuitive and accurate matching results.

• Publications of The Korean Astronomical Society
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• v.21 no.1
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• pp.1-9
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• 2006

An archiving system designed to enable documenting database of astronomical images, with functions of search and download, is being developed by Korean Astronomical Data Center(KADC) of Korea Astronomy and Space Science Institute(KASI). The system consists of three PCs for web server, database server, and system management server. The search program for the web environment is operated in the web server. In the management server, several utility program we developed are installed: input program for the database, program for transfer from fits to jpg files, program for data recovery and management, and programs for statistics and connect management. The collected data would be sorted out by the system manager to input into the database. The online input is possible in an observatory where the data is produced. We applied the content management system(CMS) module for the database management. On the basic of CMS module, we set up a management system for the whole life cycle of metadata from creation and collection to storage and deletion of the data. For the search function, we employed a technique to extract indices from the metadata. In addition, MySQL is adopted for DBMS. We currently display about 2,700 and 25,000 photographs for astronomical phenomena and astronomical objects on the data, respectively.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.589-598
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• 2002

The color measuring/matching expert system is implemented with a new color measuring method that combines intelligent algorithms with image processing techniques. Color measuring part of the proposed system preprocesses the scanned original color input images to eliminate their distorted components by means of the image histogram technique of image pixels, and then extracts RGB(Red, Green, Blue)data among color information from preprocessed color input images. If the extracted RGB color data does not exist on the matching recipe databases, we can measure the colors for the user who want to implement the model that can search the rules for the color mixing information, using the intelligent modeling techniques such as fuzzy inference system and adaptive neuro-fuzzy inference system. Color matching part can easily choose images close to the original color for the user by comparing information of preprocessed color real input images with data-based measuring recipe information of the expert, from the viewpoint of the delta Eformula used in practical process.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.3
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• pp.500-508
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• 2008

For efficient compatible system between medical clinics, the medical information has to be built on a standardized protocol such as a HL7 for text data and a DICOM for image data. But it is difficult to exchange information between medical clinics because the systems and softwares are different and also a structure of data and a type of code. Therefore we analyze a structure of DICOM file and design an integrated database for effective information sharing and exchange. The WISD system suggested in this paper separate the DICOM file transmitted by medical clinics to text data and image data and store it in the integrated DB(database) by standardized protocol respectively. It is very efficient that each medical clinic can search and exchange information by web browser using the suggested system. The WISD system can not only search and control of image data and patient information through integrated database and internet, but share medical information without extra charge like construction of new system.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.40-48
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• 2021

Content-Based Image Retrieval (CBIR) system plays a vital role to retrieve the relevant images as per the user perception from the huge database is a challenging task. Images are represented is to employ a combination of low-level features as per their visual content to form a feature vector. To reduce the search time of a large database while retrieving images, a novel image retrieval technique based on feature dimensionality reduction is being proposed with the exploit of metaheuristic optimization techniques based on Genetic Algorithm (GA), Extended Binary Cuckoo Search (EBCS) and Whale Optimization Algorithm (WOA). Each image in the database is indexed using a feature vector comprising of fuzzified based color histogram descriptor for color and Median binary pattern were derived in the color space from HSI for texture feature variants respectively. Finally, results are being compared in terms of Precision, Recall, F-measure, Accuracy, and error rate with benchmark classification algorithms (Linear discriminant analysis, CatBoost, Extra Trees, Random Forest, Naive Bayes, light gradient boosting, Extreme gradient boosting, k-NN, and Ridge) to validate the efficiency of the proposed approach. Finally, a ranking of the techniques using TOPSIS has been considered choosing the best feature selection technique based on different model parameters.