Abstract
In recent years, the health of many people is damaged by asbestos. Therefore, to detect very small quantity of asbestos that exists in general environment is very important. According to an officially fixed way, existence of asbestos in a certain building material is discriminated according to whether there are more than 4 crystals of asbestos per 3000 particles in samples made with crushing a part of the building material. The particle counting is performed manually, therefore it needs great time and labor. For automation, some studies to count particle with image processing are performed. To ensure consistency with conventional manual method, the automated method should be able to obtain equivalent outcome to manual methods. In this paper, we propose an automatic particle count method based on multiresolution analysis. At first, the classifier which can distinguish existence or nonexistence of a particle at the center of ROI (region of interest) is constructed. Next, the image is scanned with the classifier on multiresolution, and small areas containing a particle are found. To construct the classifier according to the counting result by manual method, we can achieve the result as same as manual one by the proposed method. To confirm validity of the proposed method, we did some experiments to apply the method to the images that particles are identified manually. As the result, we confirmed that 10% of false positive and false negative are contained respectively. Because the proportions are roughly same, the total count is as same as manual counting.
