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Please use this identifier to cite or link to this item: http://hdl.handle.net/UCSP/15839
Title: Morphological Operators Applied to Human Body Detection HOG Method Improvement
Authors: Tejada Begazo, Maria
Cervantes Jilaja, Claudia
Patiño Escarcina, Raquel Esperanza
Barrios Aranibar, Dennis
Keywords: Security systems;Human bodies;Human body detections;Method improvement;Morphological operator;Pedestrian detection;Recognition algorithm;Vertical positions;Video surveillance;Robotics
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers Inc.
metadata.dc.relation.uri: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964355780&doi=10.1109%2fLARS-SBR.2015.57&partnerID=40&md5=9e40e0a8763d0796c46577f9166d7a45
Abstract: The HOG method is applied in the detection of human bodies, specially when they are in a vertical position and in many backgrounds. HOG method was evaluated before in different applications such as pedestrian detection, video surveillance, search and rescue. However, when human bodies are in other positions, most of the time, body recognition algorithms present fails. The main idea presented in this research, is the evaluation of different morphological operators applied to improve the HOG method. These experiments show that the results of combining HOG method with morphological operators are better than just using the HOG method. In this research the HOG method combined with morphological operator close (86, 62%) and Erode (84, 35%) had better results than HOG without this pre-processing (77, 32%). © 2015 IEEE.
URI: http://repositorio.ucsp.edu.pe/handle/UCSP/15839
ISBN: urn:isbn:9781467371292
Appears in Collections:Artículos - Ciencia de la computación

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