Asbestos Detection Method with Frequency Analysis for Microscope Images

  • Authors:

  • Hikaru Kumagai;Soichiro Morishita;Kuniaki Kawabata;Hajime Asama;Taketoshi Mishima

  • Affiliations:

  • Saitama University, Saitama, Japan;The University of Tokyo, Chiba, Japan;RIKEN, Saitama, Japan;The University of Tokyo, Chiba, Japan;Saitama University, Saitama, Japan

  • Venue:
  • ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
  • Year:
  • 2009

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Abstract

In this paper, we propose an asbestos detection method focusing on frequency distribution of microscopic images. In building construction, asbestos has been used for molding plates and heat insulation materials. However, increased injury caused by asbestos has become a problem in Japan. Removal of asbestos from building materials and rendering it harmless are common means of alleviating asbestos hazards. Nevertheless, those processes necessitate a judgment of whether asbestos is included in building materials. According to the JIS standards, it is necessary to count 3000 particles in microscopic images. We consider the asbestos shape, and define a new feature obtained through frequency analysis. The proposed method intensifies the low-brightness asbestos using its feature, so it can detect not only high-brightness particles and asbestos but also low-brightness asbestos. We underscore the effectiveness of the method by comparing its results with results counted by an expert.