• Title/Summary/Keyword: ART2 algorithm

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Content-based Image Retrieval Using HSI Color Space and Neural Networks (HSI 컬러 공간과 신경망을 이용한 내용 기반 이미지 검색)

  • Kim, Kwang-Baek;Woo, Young-Woon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.5 no.2
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    • pp.152-157
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    • 2010
  • The development of computer and internet has introduced various types of media - such as, image, audio, video, and voice - to the traditional text-based information. However, most of the information retrieval systems are based only on text, which results in the absence of ability to use available information. By utilizing the available media, one can improve the performance of search system, which is commonly called content-based retrieval and content-based image retrieval system specifically tries to incorporate the analysis of images into search systems. In this paper, a content-based image retrieval system using HSI color space, ART2 algorithm, and SOM algorithm is introduced. First, images are analyzed in the HSI color space to generate several sets of features describing the images and an SOM algorithm is used to provide candidates of training features to a user. The features that are selected by a user are fed to the training part of a search system, which uses an ART2 algorithm. The proposed system can handle the case in which an image belongs to several groups and showed better performance than other systems.

Health Diagnosis System of Pet Dog Using ART2 Algorithm (ART2 알고리즘을 이용한 애견 진단 시스템)

  • Oh, Sei-Woong;Kim, Ji-Hong
    • Journal of Digital Contents Society
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    • v.10 no.2
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    • pp.327-332
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    • 2009
  • In this paper, we propose the diagnosis system that can predict pet's state of health for pet lovers lacking a technical knowledge of dog-diseases. The proposed system deduces diseases of dogs from input symptoms by our database constructed with 105 kinds of diseases and symptoms. First, a disease is clustered by ART2, the self-learning method in neural network and secondly, the result values, outputs and the weight values clustered by the algorithm are stored to database. Finally, our system diagnoses the state of health by means of comparing the learned information of diseases with the input vectors of each symptom and the related results of questions on diseases. The correct information of diseases and symptom diagnosing is important to predict the state of health of dogs. Therefore, in this paper, the proposed system can manage symptoms and diseases efficiently by database and ART2. We ask veterinary specialist with the efficiency of our system. As a result, we could confirm the possibility as the auxiliary diagnosis system for dog diseases.

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Adaptive Intrusion Detection System Based on SVM and Clustering (SVM과 클러스터링 기반 적응형 침입탐지 시스템)

  • Lee, Han-Sung;Im, Young-Hee;Park, Joo-Young;Park, Dai-Hee
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.2
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    • pp.237-242
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    • 2003
  • In this paper, we propose a new adaptive intrusion detection algorithm based on clustering: Kernel-ART, which is composed of the on-line clustering algorithm, ART (adaptive resonance theory), combining with mercer-kernel and concept vector. Kernel-ART is not only satisfying all desirable characteristics in the context of clustering-based IDS but also alleviating drawbacks associated with the supervised learning IDS. It is able to detect various types of intrusions in real-time by means of generating clusters incrementally.

A Car License Plate Recognition Using Colors Information, Morphological Characteristic and Neural Network (컬러 정보 및 형태학적 특징과 신경망을 이용한 차량 번호판 인식)

  • Cho, Jae-Hyun;Yang, Hwang-Kyu
    • The Journal of the Korea institute of electronic communication sciences
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    • v.5 no.3
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    • pp.304-308
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    • 2010
  • In this paper, we propose a new method of recognizing the vehicle license plate using color space, morphological characteristics and ART2 algorithm. Morphological characteristics of old and/or new style vehicle license plate among the candidate regions are applied to remove noise areas using 8-directional contour tracking algorithm, then follow by the extraction of vehicle plate. From the extracted license plate area, plate morphological characteristics of each region are removed. After that, labeling algorithm to extract the individual characters are then combined. The classified individual character and numeric codes are applied to the ART2 algorithm for the learning and recognition. In order to evaluate the performance of our proposed extraction and recognition of vehicle license method, we have run experiments on 100 green plates and white plates. Experimental results shown that the proposed license plate extraction and recognition method was effective.

Self Disease Diagnosis System Using Enhanced ART2 Algorithm (개선된 ART2 알고리즘을 이용한 자가 질병 진단 시스템)

  • Kim, Kwang-Baek;Woo, Young-Woon;Kim, Ju-Sung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.11
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    • pp.2150-2157
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    • 2007
  • In this paper, we have proposed a self disease diagnosis system for ordinary persons to help the decision of access methods to a specialized medical management, and for medical specialities to discover new diseases and their symptoms easily, using verification of an individual#s health status by a series of processes performed by oneself. In the proposed self disease diagnosis system, illness is decided by 60 kinds of diseases selected using the report called #Diseases that Koreans take seriously# published by Ministry of Health & Welfare and medical contents called #Engel Pharm#, and also using 161 representative symptoms for the 60 kinds of diseases. An individual#s health information is extracted by diagnosis of one#s health status by a clustering of the 60 kinds of diseases using enhanced ART2 algorithm and input vectors from the results of questions for symptoms of each disease.

Intelligent Immigration Control System by Using Passport Recognition and Face Verification

  • Kim, Kwang-Beak
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.2
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    • pp.240-246
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    • 2006
  • This paper proposes the intelligent immigration control system that authorizes the traveler through immigration and detects forged passports by using automatic recognition of passport codes, the passport photo and face verification. The proposed system extracts and deskewes the areas of passport codes from the passport image. This paper proposes the novel ART algorithm creating the adaptive clusters to the variations of input patterns and it is applied to the extracted code areas for the code recognition. After compensating heuristically the recognition result, the detection of forged passports is achieved by using the picture and face verification between the passport photo extracted from the passport image and the picture retrieved from the database based on the recognized codes. Due to the proposed ART algorithm and the heuristic refinement, the proposed system relatively shows better performance.

Various Fault Detection of Ceramic Image using ART2 (ART2를 이용한 세라믹 영상에서의 다양한 결함 검출)

  • Kim, Ju-Hyeok;Han, Min-Su;Woo, Young-Woon;Kim, Kwang-Baek
    • Proceedings of the Korean Society of Computer Information Conference
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    • pp.271-273
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    • 2013
  • 본 논문에서는 비파괴 검사를 통하여 얻은 세라믹 영상에 퍼지 기법과 ART2 기법을 적용하여 결함을 검출하는 방법을 제안한다. 제안된 방법은 세라믹 소재로 얻어진 영상에서 결함의 구간을 설정하기 위해 퍼지 스트레칭 기법을 적용하여 명암도를 대비시킨다. 명암 대비가 강조된 영상에서 퍼지 이진화 기법을 적용한 후, 상/하 경계선에 가장 많이 분포된 곳을 Max, Min으로 설정하고, Max+20, Min-20을 결함 구간으로 설정한다. 설정한 결함 구간 내의 비파괴 세라믹 영상에서 ART2 알고리즘 기법을 적용하여 세라믹 영상의 결함을 검출한다. 본 논문에서 제안된 방법을 비파괴 세라믹 영상을 대상으로 실험한 결과, 제안된 방법이 기존의 세라믹 결함 검출 방법보다 비파괴 세라믹 영상에서 다양한 형태의 결함이 검출되는 것을 확인하였다.

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Setting Method of Vigilance Parameter of ART2 Algorithm (ART2 알고리즘에서의 경계 변수 설정 방법)

  • Park, Seong-Yeol;Kim, Seong-Hoon;Kim', Kwang-Baek
    • Proceedings of the Korean Society of Computer Information Conference
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    • pp.31-34
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    • 2009
  • ART2 알고리즘은 신경 회로망 모델로서 실시간 학습이 가능하여 저속 및 고속을 지원할 뿐만 아니라 지역 최소화(local minima) 문제가 발생하지 않는 장점을 갖는다. 그러나 ART2 알고리즘은 경계 변수 설정에 따라 클러스터의 수가 달라지며, 이러한 경계 변수 설정은 패턴의 분류와 인식 성능을 좌우한다. 따라서 본 논문에서는 ART2 알고리즘에서 효율적으로 경계 변수를 설정하기 위해 패턴셋 설정을 통한 경계 변수 설정 방법을 제안한다. 제안된 경계 변수 설정 방법의 성능을 평가하기 위해 숫자 및 영문 패턴을 대상으로 실험한 결과, 패턴 분류의 성능이 기존의 방식 보다 개선된 것을 확인하였다.

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Learning Performance Improvement of Fuzzy RBF Network (퍼지 RBF 네트워크의 학습 성능 개선)

  • Kim Kwang-Baek
    • Journal of Korea Multimedia Society
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    • v.9 no.3
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    • pp.369-376
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    • 2006
  • In this paper, we propose an improved fuzzy RBF network which dynamically adjusts the rate of learning by applying the Delta-bar-Delta algorithm in order to improve the learning performance of fuzzy RBF networks. The proposed learning algorithm, which combines the fuzzy C-Means algorithm with the generalized delta learning method, improves its learning performance by dynamically adjusting the rate of learning. The adjustment of the learning rate is achieved by self-generating middle-layered nodes and by applying the Delta-bar-Delta algorithm to the generalized delta learning method for the learning of middle and output layers. To evaluate the learning performance of the proposed RBF network, we used 40 identifiers extracted from a container image as the training data. Our experimental results show that the proposed method consumes less training time and improves the convergence of teaming, compared to the conventional ART2-based RBF network and fuzzy RBF network.

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2.5D Quick Turnaround Engraving System through Recognition of Boundary Curves in 2D Images (2D 이미지의 윤곽선 인식을 통한 2.5D 급속 정밀부조시스템)

  • Shin, Dong-Soo;Chung, Sung-Chong
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.20 no.4
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    • pp.369-375
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    • 2011
  • Design is important in the IT, digital appliance, and auto industries. Aesthetic and art images are being applied for better quality of the products. Most image patterns are complex and much lead-time is required to implement them to the product design process. A precise reverse engineering method generating 2.5D engraving models from 2D artistic images is proposed through the image processing, NURBS interpolation and 2.5D reconstruction methods. To generate 2.5D TechArt models from the art images, boundary points of the images are extracted by using the adaptive median filter and the novel MBF (modified boundary follower) algorithm. Accurate NURBS interpolation of the points generates TechArt CAD models. Performance of the developed system has been confirmed through the quick turnaround 2.5D engraving simulation linked with the commercial CAD/CAM system.