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Please use this identifier to cite or link to this item: http://hdl.handle.net/UCSP/15824
Title: A Semi-Automated Approach for Recognizing Moving Targets Using a Global Vision System
Authors: Ripas Mamani, Roger
Cervantes Jilaja, Claudia
Rosas Cuevas, Yessica
Patiño Escarcina, Raquel Esperanza
Barrios Aranibar, Dennis
Keywords: Color;Computer vision;Image processing;Image segmentation;Interactive computer systems;Real time systems;Robot applications;Robotics;Robots;Sports;Video signal processing;Automated approach;Automated process;Color segmentationColor space; External characteristic; Image calibration; Moving targets; Soccer robot, Automation;Color space;External characteristic;Image calibration;Moving targets;Soccer robot;Automation
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers Inc.
metadata.dc.relation.uri: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85010443455&doi=10.1109%2fLARS-SBR.2016.10&partnerID=40&md5=f2e438eb2202dc7018f9d7fe0d36b623
Abstract: Global vision system works with processes of sorting, recognition and identification through some external characteristics as: color, shape and size depending of specific targets. In this paper we propose a semi-automated approach to recognize the targets in moving, where first is performed the image calibration with respect to the lighting and then proceeds to recognize a variety of colors and sizes, through several channels of different color spaces in the processing of video sequences to recognize moving targets, using the proposed algorithm called Color Segmentation (Algorithm 1) to identify a variety of light and dark colors. After semi-automated process is performed the sorting or recognizing of the moving target, where is obtained the position (x, y) of central point and the size of the area (pixels) of the segmentation region. Tests were conducted in: the location of robots in a soccer robot environment (with 94.36% of accuracy) and chestnuts selection process (with 91.80% of accuracy), if the image needs to recognize more than five detections then it proceeds to add parallelism, i.e. add a thread for each segmented color, thus improving processing time. © 2016 IEEE.
URI: http://repositorio.ucsp.edu.pe/handle/UCSP/15824
ISBN: 9781509036561
Appears in Collections:Artículos de investigación

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