Wavelet-based corner detection technique using optimal scale
Pattern Recognition Letters
Wavelet-based corner detection using eigenvectors of covariance matrices
Pattern Recognition Letters
Focus-of-Attention from Local Color Symmetries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition Letters
Distributed recursive learning for shape recognition through multiscale trees
Image and Vision Computing
Multiscale contour corner detection based on local natural scale and wavelet transform
Image and Vision Computing
A feature-based matching scheme: MPCD and robust matching strategy
Pattern Recognition Letters
Contour simplification using a multi-scale local phase analysis
Image and Vision Computing
Feature point detection utilizing the empirical mode decomposition
EURASIP Journal on Advances in Signal Processing
Robust image corner detection based on scale evolution difference of planar curves
Pattern Recognition Letters
Revisiting ShortStraw: improving corner finding in sketch-based interfaces
Proceedings of the 6th Eurographics Symposium on Sketch-Based Interfaces and Modeling
Automated freehand sketch segmentation using radial basis functions
Computer-Aided Design
Unsupervised image categorization
Image and Vision Computing
Corner detection based on gradient correlation matrices of planar curves
Pattern Recognition
Partially occluded object recognition
International Journal of Computer Applications in Technology
Technical Section: SpeedSeg: A technique for segmenting pen strokes using pen speed
Computers and Graphics
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
Feature point extraction from the local frequency map of an image
Journal of Electrical and Computer Engineering
Classification of underwater signals using wavelet transforms and neural networks
Mathematical and Computer Modelling: An International Journal
Multiscale Corner Detection in Planar Shapes
Journal of Mathematical Imaging and Vision
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A multiscale corner detection algorithm based on the wavelet transform of contour orientation is proposed. It can utilize both the information of the local extrema and modulus of transform results to detect corners and arcs effectively. The ramp-width of contour orientation profile, which can be computed using the transformed modulus of two scales, reveals the difference between corner and arc and is utilized in the determination of corner points. The experimental results have shown that the detector is more effective than both the single- and multiple-scale detectors. They also demonstrate that the detector is insensitive to boundary noise. In addition, the proposed method is more efficient than the other multiscale corner detector because it operates on fewer number of scales, which can be implemented by a fast transform algorithm