• Title, Summary, Keyword: ART2 algorithm

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Recognition of Car Plate using Gray Brightness Variation, HSI Information and Enhanced ART2 Algorithm (명암도 변화 및 HSI 정보와 개선된 ART2 알고리즘을 이용한 차량 번호판 인식)

  • 김광백;김영주
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.5
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    • pp.379-387
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    • 2001
  • We proposed an enhanced extraction method of vehicle plate, in which both the brightness variation of gray and the Hue value of HSI color model were used. For the extraction of the vehicle plate from a vehicle image, first of all, candidate regions for the vehicle plate were extracted from the image by using the property of brightness variation of the image. A real place region was determined among candidate regions by the density of pixels with the Hue value of green and white. For- extracting the feature area containing characters from the extracted vehicle plate, we used the histogram-based approach of individual characters. And we proposed and applied for the recognition of characters the enhanced ART2 algorithm which support the dynamical establishment of the vigilance threshold with the genera]iced union operator of Yager. In addition, we propose an enhanced SOSL algorithm which is integrated both enhanced ART2 and supervised learning methods. The performance evaluation was performed using 100's real vehicle images and the evaluation results demonstrated that the extraction rates of tole proposed extraction method were improved, compared with that of previous methods based un brightness variation, RGB and HSI individually . Furthermore, the recognition rates of the proposed algorithms were improved much more than that of the conventional ART2 and BP algorithms.

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Recognition of Passports using CDM Masking and ART2-based Hybrid Network

  • Kim, Kwang-Baek;Cho, Jae-Hyun;Woo, Young-Woon
    • Journal of information and communication convergence engineering
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    • v.6 no.2
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    • pp.213-217
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    • 2008
  • This paper proposes a novel method for the recognition of passports based on the CDM(Conditional Dilation Morphology) masking and the ART2-based RBF neural networks. For the extraction of individual codes for recognizing, this paper targets code sequence blocks including individual codes by applying Sobel masking, horizontal smearing and a contour tracking algorithm on the passport image. Individual codes are recovered and extracted from the binarized areas by applying CDM masking and vertical smearing. This paper also proposes an ART2-based hybrid network that adapts the ART2 network for the middle layer. This network is applied to the recognition of individual codes. The experiment results showed that the proposed method has superior in performance in the recognition of passport.

Extraction of Basic Insect Footprint Segments Using ART2 of Automatic Threshold Setting (자동 임계값 설정 ART2를 이용한 곤충 발자국의 인식 대상 영역 추출)

  • Shin, Bok-Suk;Cha, Eui-Young;Woo, Young-Woon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.8
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    • pp.1604-1611
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    • 2007
  • In a process of insect footprint recognition, basic footprint segments should be extracted from a whole insect footprint image in order to find out appropriate features for classification. In this paper, we used a clustering method as a preprocessing stage for extraction of basic insect footprint segments. In general, sizes and strides of footprints may be different according to type and sire of an insect for recognition. Therefore we proposed an improved ART2 algorithm for extraction or basic insect footprint segments regardless of size and stride or footprint pattern. In the proposed ART2 algorithm, threshold value for clustering is determined automatically using contour shape of the graph created by accumulating distances between all the spots of footprint pattern. In the experimental results applying the proposed method to two kinds of insect footprint patterns, we could see that all the clustering results were accomplished correctly.

Limitations of Site-Specificity in Minimal Art: Focusing on Donald Judd's works (미니멀 아트의 장소특정성의 한계 : 도널드 저드의 작품을 중심으로)

  • Park, Mi Ye
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.35 no.2
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    • pp.93-104
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    • 2019
  • Minimal art, which began to flourish in the mid-1960s, explores perceptual situations caused by the involvement of objects in given site contexts. This has led to the mentions of minimal art as a site-specific art, but its limitations have also been pointed out. This study specifically addresses the limitations of minimal art as a site-specific art with two perceptual points of view. First, according to Michael Fried, situations described as 'now here' focus largely on the bodily experiences of a place. However, they do not rooted in specific time and space of a certain place. Second, the unique characteristics of a certain place are excluded from the perception of the body which occupies the passage of time. Self-sufficient algorithm, which is far from site-specific conditions, is the autonomous system creating the period in the way of arrangement of objects. In addition, Minimal art regards a body only as the objectivity excluding the subjectivity which is essential creating meaning in a place. In the latter part of the article, these features are dealt with through Donald Judd's works. This study on site-specificity also provides a new perspective on the discussion of Minimal architecture and Minimal landscape.

Appendix Extraction from Ultrasound Image using ART2 (ART2 알고리즘을 이용한 초음파 영상에서의 충수 추출)

  • Kim, Kwang Baek
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.11
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    • pp.2540-2545
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    • 2015
  • In this paper, we propose a novel method to extract appendix from ultrasound image automatically to avoid such subjectivity issue. In the process, we apply a series of image processing algorithms such as Ends_in search stretching for emphasizing brightness contrast and binarization, region labelling, and cubic spline interpolation for extracting lower bound fasicia line that is the base of extracting the appendix. Knowing that the appendix is located at the lower organ area below the bottom fascia line, we conduct a series of image processing techniques to find the fascia line correctly. And then we apply ART2 algorithm to the organ area in order to extract appendix accurately. Through experiment, the effectiveness of the proposed method is verified based on the field experts' evaluations.

Recognition of Identifiers from Shipping Container Image by Using Fuzzy Binarization and ART2-based RBF Network

  • Kim, Kwang-Baek
    • Journal of Intelligence and Information Systems
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    • v.9 no.2
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    • pp.1-18
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    • 2003
  • The automatic recognition of transport containers using image processing is very hard because of the irregular size and position of identifiers, diverse colors of background and identifiers, and the impaired shapes of identifiers caused by container damages and the bent surface of container, etc. We proposed and evaluated the novel recognition algorithm of container identifiers that overcomes effectively the hardness and recognizes identifiers from container images captured in the various environments. The proposed algorithm, first, extracts the area including only all identifiers from container images by using CANNY masking and bi-directional histogram method. The extracted identifier area is binarized by the fuzzy binarization method newly proposed in this paper and by applying contour tracking method to the binarized area, container identifiers which are targets of recognition are extracted. We proposed and applied the ART2-based RBF network for recognition of container identifiers. The results of experiment for performance evaluation on the real container images showed that the proposed algorithm has more improved performance in the extraction and recognition of container identifiers than the previous algorithms.

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Mounted PCB Classification System Using Wavelet and ART2 Neural Network (웨이브렛과 ART2 신경망을 이용한 실장 PCB 분류 시스템)

  • Kim, Sang-Cheol;Jeong, Seong-Hwan
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.5
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    • pp.1296-1302
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    • 1999
  • In this paper, we propose an algorithms for the mounted PCB classification system using wavelet transform and ART2 neural network. The feature informations of a mounted PCB can be extracted from the coefficient matrix of wavelet transform adapted subband concept. As the preprocessing process, only the PCB area in the input image is extracted by histogram method and the feature vectors are composed of using wavelet transform method. These feature vectors are used as the input vector of ART2 neural network. In the experiment using 55 mounted PCB images, the proposed algorithm shows 100% classification rate at the vigilance parameter $\rho$=0.99. The proposed algorithm has some advantages of the feature extraction in the compressed domain and the simplification of processing steps.

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A Study on Design and Implementation of Speech Recognition System Using ART2 Algorithm

  • Kim, Joeng Hoon;Kim, Dong Han;Jang, Won Il;Lee, Sang Bae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.2
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    • pp.149-154
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    • 2004
  • In this research, we selected the speech recognition to implement the electric wheelchair system as a method to control it by only using the speech and used DTW (Dynamic Time Warping), which is speaker-dependent and has a relatively high recognition rate among the speech recognitions. However, it has to have small memory and fast process speed performance under consideration of real-time. Thus, we introduced VQ (Vector Quantization) which is widely used as a compression algorithm of speaker-independent recognition, to secure fast recognition and small memory. However, we found that the recognition rate decreased after using VQ. To improve the recognition rate, we applied ART2 (Adaptive Reason Theory 2) algorithm as a post-process algorithm to obtain about 5% recognition rate improvement. To utilize ART2, we have to apply an error range. In case that the subtraction of the first distance from the second distance for each distance obtained to apply DTW is 20 or more, the error range is applied. Likewise, ART2 was applied and we could obtain fast process and high recognition rate. Moreover, since this system is a moving object, the system should be implemented as an embedded one. Thus, we selected TMS320C32 chip, which can process significantly many calculations relatively fast, to implement the embedded system. Considering that the memory is speech, we used 128kbyte-RAM and 64kbyte ROM to save large amount of data. In case of speech input, we used 16-bit stereo audio codec, securing relatively accurate data through high resolution capacity.

An Efficient Smart Phone Applications Executing Method by ART2 Algorithm (ART2 알고리즘을 이용한 효율적인 스마트폰 어플리케이션 실행 방법)

  • Kim, Kwang-Beak
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.4
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    • pp.569-574
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    • 2013
  • With probably too many smart phone applications downloaded, it is sometimes frustrating to find frequently used applications quickly. In this paper, we propose a learning application that learns what applications a user frequently uses and match them with several signals that user designated. This learning applications uses ART2 algorithm that is good for stable real-time learning. By executing this learning application, a user simply chooses an application that is to be quickly searched and then draw a figure that would match the designated application at the upper left corner of our learning application. The proposed learning application transforms the background with 0's and the figure with 1's and normalize them to be used as inputs for ART2 and ART2 does clustering to setup a match table between applications and figures. After learning, a user simply draws a figure to execute one's frequently used application.

Recognition of Identifiers from Shipping Container Image by Using Fuzzy Binarization and ART2-based RBF Network

  • Kim, Kwang-baek;Kim, Young-ju
    • Proceedings of the KAIS Fall Conference
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    • pp.88-95
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    • 2003
  • The automatic recognition of transport containers using image processing is very hard because of the irregular size and position of identifiers, diverse colors of background and identifiers, and the impaired shapes of identifiers caused by container damages and the bent surface of container, etc. We proposed and evaluated the novel recognition algorithm of container identifiers that overcomes effectively the hardness and recognizes identifiers from container images captured in the various environments. The proposed algorithm, first, extracts the area including only all identifiers from container images by using CANNY masking and bi-directional histogram method. The extracted identifier area is binarized by the fuzzy binarization method newly proposed in this paper and by applying contour tracking method to the binarized area, container identifiers which are targets of recognition are extracted. We proposed and applied the ART2-based RBF network for recognition of container identifiers. The results of experiment for performance evaluation on the real container images showed that the proposed algorithm has more improved performance in the extraction and recognition of container identifiers than the previous algorithms.

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