計算幾何を用いた高品質イメージ検索システムに関する研究
Project/Area Number 
12J07851

Research Category 
GrantinAid for JSPS Fellows

Allocation Type  Singleyear Grants 
Section  国内 
Research Field 
Fundamental theory of informatics

Research Institution  Tohoku University 
Research Fellow 
ガオタントン ナスダ 東北大学, 大学院情報科学研究科, 特別研究員(DC2)

Project Period (FY) 
2012 – 2013

Project Status 
Completed (Fiscal Year 2013)

Budget Amount *help 
¥1,800,000 (Direct Cost: ¥1,800,000)
Fiscal Year 2013: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 2012: ¥900,000 (Direct Cost: ¥900,000)

Keywords  Shape descritor / Pattern matching / Image retrieval / イメージ検索 / 計算幾何 / アルゴリズム / イメージセグメンテーション 
Research Abstract 
The objective of this research is to improve the quality of image retrieval in a realworld application to be as high as successful a text retrieval method. We focus on applying shape feature of main objects, which are extracted from a query image, for identifying similarity among images. Two algorithms are proposed. The first one is for improving the time complexity when applying the shape similarity measure. The second algorithm is for improving the quality of the image segmentation when using basemonotone regions. Also to allow the system to be able to automatically locate the important objects. In this research, the shape similarity measure called Modified Hausdorff Distance is applied. Given two set of boundary points P and Q, to compare the two shapes using the Modified Hausdorff Distance, one shape needs to be aligned on the other. The Modified Hausdorff Distance is the average distance of the closest points between the points on the two shape boundary. To obtain an optimal simi
… More
larity measure, the shapes must be aligned to the most similar part of each other. In a naive method, all pairs of points are applied for finding the optimal transformation. Therefore, the time complexity is cubic in the size of the boundary points. Instead of applying all possible transformation, we proposed a method which applies a pair of correspondence points for mapping the two shapes to the similar part of each other. We also proposed a shape descriptor called a Local Distance Interior Ratio (LDIR) for describing the shape between a feature point and every other boundary points. A pair of points such that the LDIR are similar is called a correspondence. By using the correspondence points, the time complexity for computing the Modified Hausdorff Distance is improved. Moreover, the quality of the retrieved result is as good as applying the naive method. To deal with the large size of image database, it is important for the system to be able to locate and extract the shape contour of the important objects in an image automatically. We proposed a semiautomatic image segmentation algorithm. We employ an algorithm called a roomedge region for removing background region. In order to segment an image containing multiple objects, it can be segmented by decomposing the given pixel grid into small subgrids and apply the roomedge region for each subgrids. One limitation is'the quality of the segmented result depends on decomposition of the subgrids. We present two algorithms for decomposing an image optimally. The first one is called a quadtree decomposition, which an image is optimally decomposed using the quadtree structure. The second on is called an optimal baseline location, which optimally placed a partition lines. In the future, we plan to apply machine learning methods and other features such as color for improving the quality of the retrieved result. Moreover, the label attached to the image is taken into consideration in order to widening the scope of the search. Less

Strategy for Future Research Activity 
(抄録なし)

Report
(2 results)
Research Products
(9 results)



[Journal Article] Base location problems for basemonotone regions2013
Author(s)
Jinhee Chun, Takashi Horiyama, Takehiro Ito, Natsuda Kaothanthong, Hirotaka Ono, Yota Otachi, Takeshi Tokuyama, Ryuhei Uehara, Takeaki Uno

Journal Title
Proc. 7th International Workshop on Algorithms and Computation (WALCOM 2013), Lecture Notes in Computer Science
Volume: 7748
Pages: 5364
DOI
Related Report
Peer Reviewed





[Presentation] Algorithms for computing optimal image segmentation using quadtree decomposition2012
Author(s)
Jinhee Chun, Takashi Horiyama, Takehiro Ito, Natsuda Kaothanthong, Hirotaka Ono, Yota Otachi, Takeshi Tokuyama, Ryuhei Uehara, Takeaki Uno
Organizer
ThailandJapan Joint Conference on Computational Geometry and Graphs (TJJCCGG)
Place of Presentation
Srinakharinwirot University, Bangkok, Thailand
Year and Date
20121206
Related Report
