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ICPR
2008
IEEE
14 years 8 months ago
Object recognition and segmentation using SIFT and Graph Cuts
In this paper, we propose a method of object recognition and segmentation using Scale-Invariant Feature Transform (SIFT) and Graph Cuts. SIFT feature is invariant for rotations, s...
Akira Suga, Keita Fukuda, Tetsuya Takiguchi, Yasuo...
IBPRIA
2005
Springer
14 years 1 months ago
Matching Deformable Regions Using Local Histograms of Differential Invariants
This paper presents a technique to enable deformable regions to be matched using image databases based on the information provided by the differential invariants of local histogram...
Nicolas Pérez de la Blanca, José M. ...
ECCV
1992
Springer
13 years 11 months ago
Data and Model-Driven Selection using Color Regions
A key problem in model-based object recognition is selection, namely, the problem of determining which regions in the image are likely to come from a single object. In this paper w...
Tanveer Fathima Syeda-Mahmood
GBRPR
2005
Springer
14 years 1 months ago
Coarse-to-Fine Object Recognition Using Shock Graphs
Shock graphs have emerged as a powerful generic 2-D shape representation. However, most approaches typically assume that the silhouette has been correctly segmented. In this paper,...
Aurelie Bataille, Sven J. Dickinson
CIARP
2007
Springer
14 years 1 months ago
Image Segmentation Using Automatic Seeded Region Growing and Instance-Based Learning
Segmentation through seeded region growing is widely used because it is fast, robust and free of tuning parameters. However, the seeded region growing algorithm requires an automat...
Octavio Gómez, Jesús A. Gonzá...