Earticle

초록

영어

In this paper, we propose a statistical scheme for recognizing three-dimensional textures shown in motion images, e.g., ultrasound imaging, which we call “dynamic textures”. The texture characteristics emerge as the distinct movement in the motion images, and the dynamic cues would be useful especially for recognizing ambiguous texture patterns in noisy images. We apply cubic higher-order auto-correlation (CHLAC) to extract features both of the textures and their movements, and then linear regression to evaluate (recognize) the texture. For the linear regression, we extend ordinary multiple regression analysis so as to reduce within-class fluctuations. In the experiment for estimating quality of beef meat by using ultrasound motion images, the proposed method exhibits the favorable performances which are close to ground truth given by the experts.

목차

Abstract
 1. Introduction
 2. Preprocessing
 3. Proposed Method for Recognizing Dynamic Textures
  3.1. Bag-of-Features Representation for Image Sequence
  3.2. Feature Extraction Method
  3.3. Linear Regression Method
 4. Experimental Result
  4.1. Experimental Setup
  4.2. Evaluation Protocol
  4.3. Results and Discussion
 5. Concluding Remarks
 References

키워드

저자

• Takumi Kobayashi [ National Institute of Advanced Industrial Science and Technology ]
• Kenji Watanabe [ National Institute of Advanced Industrial Science and Technology ]
• Tetsuya Higuchi [ National Institute of Advanced Industrial Science and Technology ]
• Nobuyuki Otsu [ National Institute of Advanced Industrial Science and Technology ]
• Tsuneharu Miyajima [ Saga Prefectural Livestock Experiment Station, Takeo, Saga, Japan ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605