A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image and Vision Computing
Precision Edge Contrast and Orientation Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision, Graphics, and Image Processing
Grey level corner detection: a generalization and a robust real time implementation
Computer Vision, Graphics, and Image Processing
On Achievable Accuracy in Edge Localization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Some Defects in Finite-Difference Edge Finders
IEEE Transactions on Pattern Analysis and Machine Intelligence
A computational approach for corner and vertex detection
International Journal of Computer Vision
On the Edge Location Error for Local Maximum and Zero-Crossing Edge Detectors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluation of Ridge Seeking Operators for Multimodality Medical Image Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
Estimation and Compensation of Subpixel Edge Localization Error
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparison of edge detectors: a methodology and initial study
Computer Vision and Image Understanding
Using Angular Dispersion of Gradient Direction for Detecting Edge Ribbons
IEEE Transactions on Pattern Analysis and Machine Intelligence
Early Jump-Out Corner Detectors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modeling Edges at Subpixel Accuracy Using the Local Energy Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge detection in untextured and textured images-a common computational framework
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A moment-based unified approach to image feature detection
IEEE Transactions on Image Processing
Local orientation analysis in images by means of the Hermite transform
IEEE Transactions on Image Processing
Edge Detection with Embedded Confidence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition Letters
Behavior of the Laplacian of Gaussian Extrema
Journal of Mathematical Imaging and Vision
Performance evaluation of corner detectors using consistency and accuracy measures
Computer Vision and Image Understanding
Extracting image orientation feature by using integration operator
Pattern Recognition
Scale multiplication in odd Gabor transform domain for edge detection
Journal of Visual Communication and Image Representation
A biologically motivated multiresolution approach to contour detection
EURASIP Journal on Applied Signal Processing
A model-based approach to junction detection using radial energy
Pattern Recognition
Improving the interest operator for face recognition
Expert Systems with Applications: An International Journal
Evaluation of visual attention models under 2D similarity transformations
Proceedings of the 2009 ACM symposium on Applied Computing
Application of Kohonen network for automatic point correspondence in 2D medical images
Computers in Biology and Medicine
Performance evaluation of corner detectors using consistency and accuracy measures
Computer Vision and Image Understanding
Restoration of images corrupted by Gaussian and uniform impulsive noise
Pattern Recognition
A simple and efficient approach to barcode localization
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
Review article: Edge and line oriented contour detection: State of the art
Image and Vision Computing
Stochastic approximation for background modelling
Computer Vision and Image Understanding
Blur-resistant joint 1D and 2D barcode localization for smartphones
Proceedings of the 12th International Conference on Mobile and Ubiquitous Multimedia
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Edges, corners, and vertices in an image correspond to 1D (one-dimensional) and 2D discontinuities in the intensity surface of the underlying scene. Ridges and peaks correspond to 1D and 2D extrema in it. All of them can be characterized by the distribution of gradients, particularly by dimensionality of it. The approach to image field categorization here is to construct a covariance matrix of the gradient vector in each small window and apply the canonical correlation analysis to it. Schwarz's inequality on the matrix determinant and the related differential equation is the key to this analysis. We obtain two operators $P_{EG}$ and $Q_{EG}$ to categorize the image field into a unidirectionally varying region (UNIVAR), an omnidirectionally varying region (OMNIVAR), and a nonvarying region. We investigate the conditions under which their absolute maximum response, i.e., $P_{EG}=1$ and $Q_{EG}=1$, occurs in the small window and show that they are, respectively, the desired 1D and 2D discontinuities/extrema and OMNIVAR, is in many cases, a 1D pattern in polar coordinates. This leads to an algorithm to obtain further classification and accurate localization of them into edges, ridges, peaks, corners, and vertices through detailed analysis in the informative (varying) axis of them. We examined and compared the performance of the operators and the localization algorithm on various types of images and various noise levels. The results indicate that the proposed method is superior with respect to stability, localization, and resolution.