Since practical multiplexed structured light systems currently available use plural light patterns or different illumination conditions to ensure a high reliability, their fast performance is impaired. This paper describes a fast, highly reliable range imaging system with a multiplexed structured light system that uses a direct space encoding approach while using only a single light pattern. Unlike a conventional encoding approach, the proposed approach is unique in that it encodes object space through the use of a special optical system which consists of field stops, plural lenses, and shield masks, rather than a light pattern. The theoretical considerations and experimental results demonstrate that the proposed approach is effective for a highly reliable, fast, accurate range imaging system
en-copyright= kn-copyright= en-aut-name=BabaMitsuru en-aut-sei=Baba en-aut-mei=Mitsuru kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=KonishiTadataka en-aut-sei=Konishi en-aut-mei=Tadataka kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= affil-num=1 en-affil= kn-affil=Okayama University affil-num=2 en-affil= kn-affil=Okayama University en-keyword=distance measurement kn-keyword=distance measurement en-keyword=image coding kn-keyword=image coding en-keyword=image sensors kn-keyword=image sensors en-keyword=imaging kn-keyword=imaging en-keyword=lenses kn-keyword=lenses en-keyword=multiplexing kn-keyword=multiplexing en-keyword=ray tracing kn-keyword=ray tracing en-keyword=shape measurement kn-keyword=shape measurement END start-ver=1.4 cd-journal=joma no-vol=3 cd-vols= no-issue= article-no= start-page=1948 end-page=1952 dt-received= dt-revised= dt-accepted= dt-pub-year=2004 dt-pub=20045 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=3D shape recognition system by ultrasonic sensor array and genetic algorithms en-subtitle= kn-subtitle= en-abstract= kn-abstract=This paper describes 3D shape recognition system using ultrasound pressure data and a Genetic Algorithm. The ultrasonic 3D shape recognition system using has commonly used a Neural Network (NN). However, a NN perform poorly when lacking learned data. In order to overcome this problem when using a NN, we here attempt to replace the NN with a Genetic Algorithm (GA). Unlike a NN, the GA can recognize shapes without depending on learned data. Experimental results demonstrate that the recognition ratios of the proposed recognition system using the GA are higher than that of a conventional 3D shape recognition system using a NN. Therefore, it is shown that our ultrasonic 3D shape recognition system is effective for many industrial applications.
en-copyright= kn-copyright= en-aut-name=BabaMitsuru en-aut-sei=Baba en-aut-mei=Mitsuru kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=OhataniKozo en-aut-sei=Ohatani en-aut-mei=Kozo kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=KomatsuSyunya en-aut-sei=Komatsu en-aut-mei=Syunya kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= affil-num=1 en-affil= kn-affil=Okayama University affil-num=2 en-affil= kn-affil=Hiroshima Institute of Technology affil-num=3 en-affil= kn-affil=Okayama Univeristy en-keyword=Ultrasonic sensor kn-keyword=Ultrasonic sensor en-keyword=3D shape recognition. Generic Algorithms kn-keyword=3D shape recognition. Generic Algorithms END