Learning flexible models from image sequences
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Wavelet-Based Affine Invariant Representation: A Tool for Recognizing Planar Objects in 3D Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hidden Markov models vs. syntactic modeling in object recognition
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
ICIIS '99 Proceedings of the 1999 International Conference on Information Intelligence and Systems
Affine-invariant B-spline moments for curve matching
IEEE Transactions on Image Processing
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
2D Affine-Invariant Contour Matching Using B-Spline Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Segmentation Based on Supernodes and Region Size Estimation
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Image contour extraction based on ant colony algorithm and B-snake
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
International Journal of Computer Applications in Technology
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In this paper, we present a novel adaptive B-Snake model for object contour extraction. A cubic B-Snake model is developed for extracting 2D deformable objects from medical images, with an adaptive control point insertion algorithm that is suggested to increase the flexibility of B-Snake to describe complex shape. This method overcomes the problems that exist in other B-spline based model that have to decide beforehand or exhaustively search over a range of value for the number of control points. Hence, these methods are less flexible to describe unknown complex shapes. A minimum energy method which we called Minimum Mean Square Error (MMSE) is proposed for B-Snake to push it to the target boundary. The internal forces are not required in deforming B-Snake since the representation of B-Spline has guaranteed smoothness by hard implicit constraints. The proposed B-Snake model has been tested on object contour extraction such as human brain ventricle in Magnetic Resonance (MR) images. The experimental results demonstrate the capability of adaptive shape description and object contour extraction.