An asbestos detection method from microscope images using support vector random field of local color features (特集 ビジョン技術の新たな潮流)

スポンサーリンク

概要

• 論文の詳細を見る

• In this paper, an asbestos detection method from microscope images is proposed. The asbestos particles have different colors in two specific angles of the polarizing plate. Therefore, human examiners use the color information to detect asbestos. To detect the asbestos by computer, we develop the detector based on Support Vector Machine (SVM) of local color features. However, when it is applied to each pixel independently, there are many false positives and negatives because it does not use the relation with neighboring pixels. To take into consideration of the relation with neighboring pixels, Conditional Random Field (CRF) with SVM outputs is used. We confirm that the accuracy of asbestos detection is improved by using the relation with neighboring pixels.

• 社団法人 電気学会の論文
• 2009-05-01

著者

• HOTTA Kazuhiro

  The University of Electro-Communications

• MORIGUCHI Yoshitaka

  The University of Electro-Communications

• TAKAHASHI Haruhisa

  The University of Electro-Communications

関連論文

• An Efficient Search Method Based on Dynamic Attention Map by Ising Model(Image Recognition and Understanding)
• Scale Invariant Face Detection and Classification Method Using Shift Invariant Features Extracted from Log-Polar Image (Special Issue on Biometric Person Authentication)
• An asbestos detection method from microscope images using support vector random field of local color features (特集 ビジョン技術の新たな潮流)

スポンサーリンク