• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.6
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• pp.961-968
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• 1987

This paper describes an intelligent image compression system called AIIC which is capable of adjusting image compression ratios ranging from 1:1 to 12,000:1 depending on available bandwidth. This system utilizes not only conventional image compression algorithms but also intelligent techniques through understanding image contents to achieve ultra-high compression ratios. This system was simulated on a micro-computer network.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.328-335
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• 2007

Ontology is represented by the shared concepts and relations among those. Many studies have been actively working on sharing human's knowledge with that of systems by using it. For a typical example, there is the design and implementation of ontology system for image understanding. However conventional studies on ontology-based image understanding have proposed not concrete methods but conceptual idea. In this paper, we propose an ontology-based image understanding system with following four processes: i)knowledge representation of a specific domain by the ontology, ii)feature extraction of objects through image processing and image analysis, iii)image interpretation by object features, and iv)reduction of ambiguity existing in image interpretation by ontology reasoning. We implement an image understanding system based on the proposed processed, and show the effectiveness of the proposed system from experimental results in a specific domain.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.235-240
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• 2004

In this paper, we propose a framework for ontological knowledge-based image understanding systems. Ontology composed of concepts can be used as a guide for describing objects from a specific domain of interest and describing relations between objects from different domains The proposed framework consists of four main subparts ⅰ) ontological knowledge bases, ⅱ) primitive feature detectors, ⅲ) concept inference engine, and ⅳ) semantic inference engine. Using ontological knowledge bases on various domains and features extracted from the detectors, concept inference engine infers concepts on regions of interest in an image and semantic inference engine reasons semantic situations between concepts from different domains. We present a outline for ontological knowledge-based image understanding systems and application examples within specific domains such as text recognition and human recognition in order to show the validity of the proposed system.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.333-335
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• 2015

A computer vision-based scene recognition algorithm is proposed for monitoring construction sites. The system analyzes images acquired from a surveillance camera to separate regions and classify them as building, ground, and hole. Mean shift image segmentation algorithm is tested for separating meaningful regions of construction site images. The system would benefit current monitoring practices in that information extracted from images could embrace an environmental context.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.571-574
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• 2003

This research is aimed to automate the generating process of the database from paper based table forms like this work. The registration table has so complicate table structures, ana in this research we used the registration tables as an example of general table structure understanding. We propose a table structure understanding system for some table types, and it has some steps. The first step is that the document images on paper are read from the image scanner. The second step is that a document image segments into some tables. In the third step, the character strings is extracted using image processing technology and the property of the character strings is determined. And the structured database is generated automatically. The proposed system consists of two systems. "Master document generation system" is used for the table form definition, and it doesn′t include the handwritten characters. "Structure analysis system for complete d table" is used for the written form, and it analyzes the table form filled in the handwritten character. We implemented the system using MS Visual C＋＋ on Windows, and it can get the correct extraction rate 98％ among 51 registration tables written by the different students.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.5
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• pp.757-772
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• 1993

This paper describes the knowledge extraction for image understanding in knowledge based system. The current set of low level processes operate on the numerical pixel arrays, to segment the image into region and to convert the image into directional image, and to calculate feature for these regions. The current set of intermedate level processes operate on the results of earlier knowledge source to build more complex representations of the data. We have grouped into thee categories : feature based classification, geometric token relation, perceptual organization and grouping.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.498-506
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• 2003

A computer vision system applied to an intelligent safety vehicle has been required to be worked on a small sized real time special purposed hardware not on a general purposed computer. In addition, the system should have a high reliability even under the adverse road traffic environment. This paper presents a design and an implementation of an onboard hardware system taking into account for high speed image processing to analyze a road traffic scene. The system is mainly composed of two parts: an early processing module of FPGA and a postprocessing module of DSP. The early processing module is designed to extract several image primitives such as the intensity of a gray level image and edge attributes in a real-time Especially, the module is optimized for the Sobel edge operation. The postprocessing module of DSP utilizes the image features from the early processing module for making image understanding or image analysis of a road traffic scene. The performance of the proposed system is evaluated by an experiment of a lane-related information extraction. The experiment shows the successful results of image processing speed of twenty-five frames of 320$\times$240 pixels per second.

• Journal of Physiology & Pathology in Korean Medicine
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• v.21 no.5
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• pp.1065-1071
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• 2007

It has been known that Asian Medicine theory are based on yin and yang & Five Phases. but recently many therapist using asian medicine in Korea or another nations, take up the position that it is not inevitable for them to adopt the theory of yin-and-yang & Five Phases when they cure a patient. but the point of this view suggests they can not understand totally the real theory about yin-and-yang & Five Phases. asian image-mathematics based on I-Ching could analysis all things with the natural number. the kernel of understanding on principle of I-Ching is realizing that the standard should be changed in some conditions and the form of cosmos should change endless. the system of all thing under sun is divided in three parts on the asian image-mathematics. the nature number from one to nine is divided in three categories that are grouped as 123, 456, 789. So, if we want to understand Five Phases theory, we suggest that it is useful to know the organic connected relations among Four Images, Five Phases, Six Qi(six kinds of weather). the aim of this paper is to arrive at understanding of profound learning on image-mathematics throughout the number of 4, 5, 6 in the concrete context.

• Korean Journal of Cognitive Science
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• v.5 no.2
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• pp.47-73
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• 1994

In this paper, a blackboard-based road image understanding system is implemented. The 7 useful information which organized by the hierarchical manner are stored in the blackboard system. The 6 Knowledge source modules and the blackboard make the communications under the supervision of the control module. For a scene, each hypothesis is generated and then verified for every meaningful object. On the simulation results, the correct recognition ratio can be reached out 90%. It shows that the extraction of road information for the autonomous navigation can be obtained using the blackboard architecture.