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» Object Recognition Using Segmentation for Feature Detection
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156
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VMV
2001
248views Visualization» more  VMV 2001»
15 years 6 months ago
Using an Extended Hough Transform Combined with a Kalman Filter to Segment Tubular Structures in 3D Medical Images
We present a new approach for the coarse segmentation of tubular structures in 3D image data. Our algorithm, which requires only few initial values and minimal user interaction, c...
Thorsten Behrens, Karl Rohr, H. Siegfried Stiehl
163
Voted
DAS
2010
Springer
15 years 3 months ago
Automatic unsupervised parameter selection for character segmentation
A major difficulty for designing a document image segmentation methodology is the proper value selection for all involved parameters. This is usually done after experimentations o...
Georgios Vamvakas, Nikolaos Stamatopoulos, Basilio...
172
Voted
TSMC
2011
292views more  TSMC 2011»
14 years 11 months ago
Circular Blurred Shape Model for Multiclass Symbol Recognition
—In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. ...
Sergio Escalera, Alicia Fornés, Oriol Pujol...
ICASSP
2011
IEEE
14 years 8 months ago
A general Bayesian algorithm for visual object tracking based on sparse features
This paper describes a Bayesian algorithm for rigid/non-rigid 2D visual object tracking based on sparse image features. The algorithm is inspired by the way human visual cortex se...
Mauricio Soto Alvarez, Carlo S. Regazzoni
161
Voted
ICRA
2010
IEEE
164views Robotics» more  ICRA 2010»
15 years 3 months ago
Boundary detection based on supervised learning
— Detecting the boundaries of objects is a key step in separating foreground objects from the background, which is useful for robotics and computer vision applications, such as o...
Kiho Kwak, Daniel F. Huber, Jeongsook Chae, Takeo ...