Distance transformations in digital images
Computer Vision, Graphics, and Image Processing
Classification of Partial 2-D Shapes Using Fourier Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Partial Shape Recognition Using Dynamic Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Use neural networks to determine matching order for recognizing overlapping objects
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hidden Markov Models with Spectral Features for 2D Shape Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parallel distance transforms on a linear array architecture
Information Processing Letters
Automation and Remote Control
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Exact corner location using attentional generalized symmetry transform
Pattern Recognition Letters
Alignment-Based Recognition of Shape Outlines
IWVF-4 Proceedings of the 4th International Workshop on Visual Form
Learning Shape Models from Examples
Proceedings of the 23rd DAGM-Symposium on Pattern Recognition
BAS: a perceptual shape descriptor based on the beam angle statistics
Pattern Recognition Letters
Proceedings of the 13th annual ACM international conference on Multimedia
Integral Invariants for Shape Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
2D Euclidean distance transform algorithms: A comparative survey
ACM Computing Surveys (CSUR)
Natural landmark extraction for mobile robot navigation based on an adaptive curvature estimation
Robotics and Autonomous Systems
Curve matching for open 2D curves
Pattern Recognition Letters
Rolling penetrate descriptor for shape-based image retrieval and object recognition
Pattern Recognition Letters
A robust approach for automatic detection and segmentation of cracks in underground pipeline images
Image and Vision Computing
Matching occluded objects invariant to rotations, translations, reflections, and scale changes
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Fuzzy morphology for edge detection and segmentation
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Piecewise approximation of contours through scale-space selection of dominant points
IEEE Transactions on Image Processing
Partially occluded object recognition
International Journal of Computer Applications in Technology
The Global-Local transformation for noise resistant shape representation
Computer Vision and Image Understanding
Future Generation Computer Systems
International Journal of Applied Mathematics and Computer Science - Computational Intelligence in Modern Control Systems
Multiple polyline to polygon matching
ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
Axial representation of character by using wavelet transform
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
Some new results on non-rigid correspondence and classification of curves
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
The monogenic curvature scale-space
IWCIA'06 Proceedings of the 11th international conference on Combinatorial Image Analysis
Multiscale Corner Detection in Planar Shapes
Journal of Mathematical Imaging and Vision
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An algorithm is presented to recognize and locate partially distorted 2D shapes without regard to their orientation, location, and size. The algorithm first calculates the curvature function from the digitized image of an object. The points of local maxima and minima extracted from the smooth curvature are used as control points to segment the boundary and to guide the boundary-matching procedure. The boundary-matching procedure considers two shapes at a time, one shape from the template databank, and the other from the object being classified. The procedure tries to match the control points in the unknown shape to those of a shape from the template databank, and estimates the translation, rotation, and scaling factors to be used to normalize the boundary of the unknown shape. The chamfer 3/4 distance transformation and a partial distance measurement scheme constitute the final step in measuring the similarity between the two shapes. The unknown shape is assigned to the class corresponding to the minimum distance. The algorithm has been successfully tested on partial shapes using two sets of data, one with sharp corners and the other with curve segments. This algorithm not only is computationally simple, but also works reasonably well in the presence of a moderate amount of noise.