Detection of Intensity Changes with Subpixel Accuracy Using Laplacian-Gaussian Masks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scaling Theorems for Zero Crossings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Uniqueness of the Gaussian Kernel for Scale-Space Filtering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Non-linearities in cortical simple cells and the possible detection of zero crossings
Biological Cybernetics
A New Sense for Depth of Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Convolution with Laplacian-of-Gaussian Masks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parsing scale-space and spatial stability analysis
Computer Vision, Graphics, and Image Processing
A VLSI architecture for computing scale space
Computer Vision, Graphics, and Image Processing
Filter-based models for pattern classification
Pattern Recognition
Computer Vision, Graphics, and Image Processing
Authenticating Edges Produced by Zero-Crossing Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge Detection and Linear Feature Extraction Using a 2-D Random Field Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Picture Processing
Detection, Localization, and Estimation of Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
``Coaxial Stereo \& Scale Based Matching''''
``Coaxial Stereo \'& Scale Based Matching''''
Computers and Electrical Engineering
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The authors propose a computational technique for the directional analysis of piecewise linear patterns in images based on the notion of zero crossings in gradient images. A given image is preprocessed by a sequence of filters that are second derivatives of 2-D Gaussian functions with different scales. This gives a set of zero-crossing maps (the scale space) from which a stability map is generated. Significant linear patterns are detected from measurements on the stability map. Information regarding orientation of the linear patterns in the image and the area covered by the patterns in specific directions is then computed. The performance of the method is illustrated through applications to a simple test image made up of straight bar patterns as well as to scanning electron microscope images of collagen fibrils in rabbit ligaments. The method has significant applications in quantitative analysis of ligament healing and in comparison of treatment methods for ligament injuries.