• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.684-685
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• 2020

영상의 세부 분류 인식에 대한 연구는 계속적으로 발전하고 있지만, 다형성의 성질을 갖는 동물에 대한 객체인식 연구는 더디게 진행되고 있다. 본 논문은 개와 고양이에 해당하는 애완동물 이미지만을 이용하여, 세부 분류인 동물의 종을 분류하는 것을 목표로 한다. 이를 위해 본 논문에서는 기계학습으로 여러 분야에서 좋은 성과를 얻고 있는 딥러닝을 이용하였으며, 그 중에서도 이미지 인식 분야에서 뛰어난 성능을 보인 Convolutional Neural Network(CNN)과 구글에서 제공하는 오픈소스 기반 딥러닝 프레임워크인 Tensorflow를 활용하였다. 제안하는 방법에 대해 37종의 애완동물 이미지, 총 7390장에 대하여 학습 및 실험하여 그 효과를 검증하였다.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.7
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• pp.847-856
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• 2017

In this paper, we propose a system to users which recommends suitable park using linguistic objects by rule-based inference engine which is made with Prolog. According to the function of city park, which provides positive elements to people such as social, psychological, environmental, and physical, Seoul city park is classified into 6 categories. The classified parks are recommended to users based on the rule based expert system. Rule-based object of park recommendation designs nine linguistic objects based on activity, multi-purposiveness, accessibility, and usage of time. This assigns allowed value accordingly. Generated rules by using these values are fired by user's preference, and infer recommended park. Information on preferences is obtained by way of dialogue, in which the user is asked questions about the three elements that are the criteria for choosing a park. As a result, through the park recommendation system, we intend to increase the user's satisfaction of using park and leisure activities.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.58-67
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• 2024

In the era of the fourth industrial revolution, data plays a vital role in enhancing the productivity of industries. To advance digitalization in the construction industry, which suffers from a lack of available data, this study proposes a model that classifies construction site photos by work types. Unlike traditional image classification models that solely rely on visual data, the model in this study includes semantic analysis of construction work types. This is achieved by extracting the significance of relationships between objects and work types from the standard construction specification. These relationships are then used to enhance the classification process by correlating them with objects detected in photos. This model improves the interpretability and reliability of classification results, offering convenience to field operators in photo categorization tasks. Additionally, the model's practical utility has been validated through integration into a classification program. As a result, this study is expected to contribute to the digitalization of the construction industry.

• Information and Communications Magazine
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• v.28 no.4
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• pp.35-40
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• 2011

본고에서는 지능형 국방 감시시스템에 적용할 수 있는 핵심 기술인 PTZ(Pan-Tilt-Zoom) 네트워크 카메라를 이용한 액티브 객체 추적 및 객체 특성 분석 기법을 소개한다. 본고에서 소개하는 기법은 기존의 적응적 배경 모델링 기반의 객체 검출에서 발생하는 고스트 현상을 제거하고 정지객체를 안정적으로 추적할 수 있는 방법과 PTZ 카메라의 Panning, Tilting, Zooming을 통하여 카메라의 FOV를 지속적으로 추적하기 위한 카메라 이동 위치 예측 알고리즘을 포함하고 있다. 본고에서는 또한, 지능형 감시시스템의 한 종류로서 일반인이 통행할 수 있는 구역에서 출입자의 의상 특성을 분석하여 비인증 출입자를 검출하는 방법과 추적하는 객체가 차량일 경우, 차량의 종류를 자동 분류하는 기법을 소개한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.583-590
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• 1999

We propose the reusability decision model of the object-oriented components, which can decide the potentiality of reusability of the object-oriented components actively. Fisrt, we select attributes for the reusability decision of the object-oriented components. Then, we acquire information from the reused components based on the quality measures and criteria proposed by many researches. Lastly, we generate algorithm for the reusability decision of the object-oriented components from the acquired information employing rough set.

• Journal of Korea Multimedia Society
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• v.12 no.4
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• pp.492-501
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• 2009

Information on movement of objects in videos can be used as an important part in categorizing and separating the contents of a scene. This paper is proposing a shape-based movement-matching algorithm to effectively find the movement of an object in video streams. Information on object movement is extracted from the object boundaries from the input video frames becoming expressed in continuous 2D shape information while individual 2D shape information is converted into a lD shape feature using the shape descriptor. Object movement in video can be found as simply as searching for a word in a text without a separate movement segmentation process using the sequence of the shape descriptor listed according to order. The performance comparison results with the MPEG-7 shape variation descriptor showed that the proposed method can effectively express the movement information of the object and can be applied to movement search and analysis applications.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.501-506
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• 2001

According to the current increase of the usefulness of information by Internet and Communication network, several methods are proposed in which multimedia information may be efficiently managed and serviced. This paper proposes FBOM(Fuzzy-Based Object Manager) using $\alpha$-cut in Object manager for Fuzzy-Based Multimedia Post-Office Box construction. The proposed system utilizes object discrimination, fuzzy filtering, and class generation structure in order to manage object using Fuzzy filtering. To know how well the proposed system are able to work, this paper have tested against the methods with 1000 items of multimedia information, and our system are compared with Random-key method and FBOM method.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.2
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• pp.209-222
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• 1999

개발 과정의 생산성과 프로그램의 신뢰성을 향상시키기 위하여 소프트웨어 재사용이 매우 중요하며 , 효과적인 재사용을 위해서 세밀한 분류 방법과 정확한 검색 방법에 기반한 객체 지향 재사용 라이브러리가 필수적이다. 본 연구에서는 재사용 라이브러리의 다중 클러스터링(multi-way clustering) 분류 방법과 클러스터 기반 선형 검색(cluster-based linear retrieval) 방법에 유전자 알고리즘(genetic algorithm)을 적용한다. 다중 클러스터링은 부품들이 할당된 클러스터 개수, 클러스터 내부 유사도 그리고 클러스터들 사이의 유사도를 최적화하는 클러스터링을 찾아 부품을 세밀히 분류하는 것이고, 클러스터 기반 선형 검색은 주어진 질의와 유사한 부품을 많이 포함하는 클러스터를 검색하는 것이다. 본 논문에서는 유전자 알고리즘이 시뮬레이티드 어닐링 알고리즘(simulated annealing algorithm) 보다 우수한 해를 찾는 것을 실험을 통하여 보이고, 또한 본 알고리즘을 이용한 CORBA 기반의 재사용 클래스 라이브러리(RCL)를 기술한다.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.588-594
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• 2021

Due to the recent proliferation of video contents, previous contents expressed as the character or the picture are being replaced to video and growth of video contents is being boosted because of emerging new platforms. As this accelerated growth has a great impact on the process of universalization of technology for ordinary people, video production and editing technologies that were classified as expert's areas can be easily accessed and used from ordinary people. Due to the development of these technologies, tasks like that recording and adjusting that depends on human's manual involvement could be automated through object tracking technology. Also, the process for situating the object in the center of the screen after finding the object to record could have been automated. Because the task of setting the object to be tracked is still remaining as human's responsibility, the delay or mistake can be made in the process of setting the object which has to be tracked through a human. Therefore, we propose a novel object tracking technique of CMT combining the face detection technique utilizing Haar cascade classifier. The proposed system can be applied to an effective and robust image tracking system for continuous object tracking on the smartphone in real time.

• Korean Journal of Remote Sensing
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• v.37 no.6_3
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• pp.2011-2025
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• 2021

In high-resolution satellite image classification, when the color values of pixels belonging to one class are different, such as buildings with various colors, it is difficult to determine the color information representing the class. In this paper, to solve the problem of determining the representative color information of a class, we propose a method to divide the color channel of HSV (Hue Saturation Value) and perform object-based classification. To this end, after transforming the input image of the RGB color space into the components of the HSV color space, the Hue component is divided into subchannels at regular intervals. The minimum distance-based image classification is performed for each hue subchannel, and the classification result is combined with the image segmentation result. As a result of applying the proposed method to KOMPSAT-3A imagery, the overall accuracy was 84.97% and the kappa coefficient was 77.56%, and the classification accuracy was improved by more than 10% compared to a commercial software.