Cross-Weighted Moments and Affine Invariants for Image Registration and Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Partial matching of planar polylines under similarity transformations
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
Ordering and Parameterizing Scattered 3D Data for B-Spline Surface Approximation
IEEE Transactions on Pattern Analysis and Machine Intelligence
BAS: a perceptual shape descriptor based on the beam angle statistics
Pattern Recognition Letters
A Graph Based Object Description for Information Retrieval in Digital Image and Video Libraries
CBAIVL '99 Proceedings of the IEEE Workshop on Content-Based Access of Image and Video Libraries
Using cross-ratios to model curve data for aircraft recognition
Pattern Recognition Letters
The Use of Force Histograms for Affine-Invariant Relative Position Description
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Efficient Parameterless Quadrilateral-Based Image Segmentation Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Polygonal shape description for recognition of partially occluded objects
Pattern Recognition Letters
2D Affine-Invariant Contour Matching Using B-Spline Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
A coarse-to-fine method for shape recognition
Journal of Computer Science and Technology
Image shape representation using curve fitting
SSIP'06 Proceedings of the 6th WSEAS International Conference on Signal, Speech and Image Processing
On Signature Invariants for Effective Motion Trajectory Recognition
International Journal of Robotics Research
Contour simplification using a multi-scale local phase analysis
Image and Vision Computing
State-of-the-art on spatio-temporal information-based video retrieval
Pattern Recognition
Rolling penetrate descriptor for shape-based image retrieval and object recognition
Pattern Recognition Letters
Motion trajectory reproduction from generalized signature description
Pattern Recognition
Dominant point detection: A new proposal
Image and Vision Computing
Probabilistic cluster signature for modeling motion classes
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
A compact shape descriptor based on the beam angle statistics
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
Shape recognition with coarse-to-fine point correspondence under image deformations
Proceedings of the 2005 joint Chinese-German conference on Cognitive systems
Representation of facial features by Catmull-Rom splines
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Piecewise approximation of contours through scale-space selection of dominant points
IEEE Transactions on Image Processing
Robust curve clustering based on a multivariate t-distribution model
IEEE Transactions on Neural Networks
The Global-Local transformation for noise resistant shape representation
Computer Vision and Image Understanding
Automated atlas-based clustering of white matter fiber tracts from DTMRI
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Geometric invariant curve and surface normalization
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
CTFDP: an affine invariant method for matching contours
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
On Hierarchical Content-Based Image Retrieval by Dynamic Indexing and Guided Search
International Journal of Cognitive Informatics and Natural Intelligence
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There have been many techniques for curve shape representation and analysis, ranging from Fourier descriptors, to moments, to implicit polynomials, to differential geometry features, to time series models, to B-splines, etc. The B-splines stand as one of the most efficient curve (surface) representations and possess very attractive properties such as spatial uniqueness, boundedness and continuity, local shape controllability, and invariance to affine transformations. These properties made them very attractive for curve representation, and consequently, they have been extensively used in computer-aided design and computer graphics. Very little work, however, has been devoted to them for recognition purposes. One possible reason might be due to the fact that the B-spline curve is not uniquely described by a single set of parameters (control points), which made the curve matching (recognition) process difficult when comparing the respective parameters of the curves to be matched. This paper is an attempt to find matching solutions despite this limitation, and as such, it deals the problem of using B-splines for shape recognition and identification from curves, with an emphasis on the following applications: affine invariant matching and classification of 2-D curves with applications in identification of aircraft types based on image silhouettes and writer-identification based on handwritten text