Earticle

초록

영어

In this paper, we propose a method for character type classification based on a probabilistic topic model. The topic model is originally developed for topic discovery in text analysis using bag-of-words representation. Recent studies have shown the model is also useful for image analysis. We adopt the probabilistic topic model for character type classification. In our method, character type classification is carried out by classifying image patches based on their topic proportions. Since the performance of the method depends on a visual vocabulary generated by image feature extraction, we compare several feature extraction and description methods, and examine the relations to classification performance. In addition, by extending the method, we propose a coarse-to-fine approach to achieve stable character type classification for a small image patch. For that purpose, firstly, we partition an image into several patches which contain enough information to estimate the model parameters via EM algorithm. Then, each patch is subdivided into smaller patches. Estimation on the small patch is carried out by MAP-technique with a prior reflecting topic proportion of its parent patch. Through the experiments, we show accurate character type classification is made possible by the probabilistic topic model.

목차

Abstract
 1. Introduction
 2. Probabilistic Topic Model
 3. Applying Probabilistic Topic Model to Images
  3.1. Bag-of-visual Words Representation and Visual Document
  3.2. Feature Extraction
 4. Character Type Classification
  4.1. Character Type Classification Method by Probabilistic Topic Model
  4.2. Classification of Small Visual Document through Coarse-to-fine Approach
 5. Experiments
  5.1. Data Sets
  5.2. Classification with pLSA Model
  5.3 Selection of Feature Detectors and Descriptors and its Effect Against Geometric Transformations
  5.4 Coarse-to-fine Approach for a Small Image Patch
 6. Conclusion
 References

키워드

저자

• Takuma Yamaguchi [ Department of Information Engineering Shinshu University ]
• Minoru Maruyama [ Department of Information Engineering Shinshu University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605