Automatic Counting Robot Development Supporting Qualitative Asbestos Analysis -Asbestos, Air Bubbles, and Particles Classification Using Machine Learning- | Zendy

Kenichi Ishizu | Zendy; Hiroshi Takemura | Zendy; Kuniaki Kawabata | Zendy; Hajime Asama | Zendy; Taketoshi Mishima | Zendy; Hiroshi Mizoguchi | Zendy

Open Access

Automatic Counting Robot Development Supporting Qualitative Asbestos Analysis -Asbestos, Air Bubbles, and Particles Classification Using Machine Learning-

Author(s) -

Kenichi Ishizu,

Hiroshi Takemura,

Kuniaki Kawabata,

Hajime Asama,

Taketoshi Mishima,

Hiroshi Mizoguchi

Publication year - 2010

Publication title -

journal of robotics and mechatronics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.257

H-Index - 19

eISSN - 1883-8049

pISSN - 0915-3942

DOI - 10.20965/jrm.2010.p0506

Subject(s) - asbestos , artificial intelligence , computer science , process (computing) , robot , qualitative analysis , asbestos fibers , computer vision , materials science , composite material , qualitative research , social science , sociology , operating system

Asbestos, particle, and air bubble counting generally supports qualitative asbestos analysis, using such procedures as dispersion staining. Operators conventionally check and count asbestos fibers visually using a microscope – a difficult, time-consuming process. The microscopic observation robot we are automating to support qualitative asbestos analysis imagesfibers and saves them automatically to a database. In this paper, we introduce image processing method using machine learning to count asbestos, particles, and air bubbles automatically.

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