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Evolutionary Learning of a Laser Pointer Detection Fuzzy System for an Environment Control System

By Francisco Chávez, Francisco Fernández, Centro Universitario De Mérida, Rafael Alcalá, Jesús Alcalá-fdez and Francisco Herrera


Abstract—Recent studies in smart homes have proposed methods to use a laser pointer for interacting with home devices, which represents a more user-friendly and less expensive home device control environment. However, detecting the laser spot on the original non-filtered images, using standard and non expensive cameras, and considering real home environments with varying conditions, is currently an open problem. In this paper we propose a hybrid technique, combining a classic technique used in image detection processes, such as Template Matching, with an evolutionary learning of a Fuzzy Rule Based Systems for the laser spot detection system in real home environments. This proposal improves the success rate in images without laser spot of the previous classical and nonclassical algorithms used for detecting the laser spot in previous works, decreasing the detection of the false offs which could lead to dangerous situations. Experimental results on a real home environment show the effectiveness of the proposed approach

Topics: Index Terms—Interaction Systems, Domotic Control Systems, Laser Pointer Detection, Fuzzy rule-based systems, Genetic Learning
Year: 2014
OAI identifier: oai:CiteSeerX.psu:
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