Automatic Laser Pointer Detection Algorithm for Environment Control Device Systems Based on Template Matching and Genetic Tuning of Fuzzy Rule-Based Systems

被引:0
|
作者
F. Chávez
F. Fernández
M.J. Gacto
R. Alcalá
机构
[1] Department of Computer Science,University of Extremadura
[2] Campus Las Lagunillas,University of Jaén, Department of Computer Science
[3] Research Center on Information and Communications Technology,University of Granada, Department of Computer Science and Artificial Intelligence
关键词
Interaction Systems; Fuzzy Rule-Based Systems; Genetic Fuzzy Systems; Laser Pointer Detection; Domotic Control Systems;
D O I
暂无
中图分类号
学科分类号
摘要
In this paper we propose a new approach for laser-based environment device control systems based on the automatic design of a Fuzzy Rule-Based System for laser pointer detection. The idea is to improve the success rate of the previous approaches decreasing as much as possible the false offs and increasing the success rate in images with laser spot, i.e., the detection of a false laser spot (since this could lead to dangerous situations). To this end, we propose to analyze both, the morphology and color of a laser spot image together, thus developing a new robust algorithm. Genetic Fuzzy Systems have also been employed to improve the laser spot system detection by means of a fine tuning of the involved membership functions thus reducing the system false offs, which is the main objective in this problem. The system presented in this paper, makes use of a Fuzzy Rule-Based System adjusted by a Genetic Algorithm, which, based on laser morphology and color analysis, shows a better success rate than previous approaches.
引用
收藏
页码:368 / 386
页数:18
相关论文
共 50 条
  • [21] A LINEAR-CONTROL ALGORITHM FOR A CLASS OF RULE-BASED SYSTEMS
    GHALLAB, M
    ESCALADAIMAZ, G
    JOURNAL OF LOGIC PROGRAMMING, 1991, 11 (02): : 117 - 132
  • [22] Structural optimization using genetic algorithms with fuzzy rule-based systems
    Chung, Tien-Tung
    Shih, Chia-Sheng
    Journal of the Chinese Society of Mechanical Engineers, Transactions of the Chinese Institute of Engineers, Series C/Chung-Kuo Chi Hsueh Kung Ch'eng Hsuebo Pao, 2007, 28 (05): : 523 - 532
  • [23] A neuro-fuzzy MAR algorithm for temporal rule-based systems
    Sisman, NA
    Alpaslan, FN
    Akman, V
    WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL 8, PROCEEDINGS: CONCEPTS AND APPLICATIONS OF SYSTEMICS, CYBERNETICS AND INFORMATICS, 1999, : 87 - 92
  • [24] Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning
    Antonio Sanz, Jose
    Fernandez, Alberto
    Bustince, Humberto
    Herrera, Francisco
    INFORMATION SCIENCES, 2010, 180 (19) : 3674 - 3685
  • [25] Decoupling of multivariable rule-based fuzzy systems
    Babuska, R
    Gegov, A
    Verbruggen, HB
    ARTIFICIAL INTELLIGENCE IN REAL-TIME CONTROL 1998, 1999, : 13 - 16
  • [26] Adaptive fuzzy rule-based classification systems
    Nozaki, K
    Ishibuchi, H
    Tanaka, H
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 1996, 4 (03) : 238 - 250
  • [27] Descriptive Stability of Fuzzy Rule-Based Systems
    Mencar, Corrado
    Castiello, Ciro
    IEEE CIS INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS 2021 (FUZZ-IEEE), 2021,
  • [28] Probabilistic reasoning in fuzzy rule-based systems
    van den Berg, J
    Kaymak, U
    van den Bergh, WM
    SOFT METHODS IN PROBABILITY, STATISTICS AND DATA ANALYSIS, 2002, : 189 - 196
  • [29] Matrix formulation of fuzzy rule-based systems
    Lotfi, A
    Andersen, HC
    Tsoi, AC
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 1996, 26 (02): : 332 - 340
  • [30] Visualization of evolving fuzzy rule-based systems
    Henzgen, Sascha
    Strickert, Marc
    Hullermeier, Eyke
    EVOLVING SYSTEMS, 2014, 5 (03) : 175 - 191