A surface specific-line tracking and slope recognition algorithm
Computer Vision, Graphics, and Image Processing
Pattern Recognition Letters
Computer techniques in neuroanatomy
Computer techniques in neuroanatomy
Scale and the differential structure of images
Image and Vision Computing - Special issue: information processing in medical imaging 1991
A computational approach for corner and vertex detection
International Journal of Computer Vision
Two-plus-one-dimensional differential geometry
VIP '94 The international conference on volume image processing on Volume image processing
Evaluation of Ridge Seeking Operators for Multimodality Medical Image Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Unbiased Detector of Curvilinear Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Gaussian Scale-Space Theory
Digital Image Processing
CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Edge Detection and Ridge Detection with Automatic Scale Selection
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Multiscale detection of curvilinear structures in 2-D and 3-D image data
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Extraction of Curved Lines from Images
ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
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Extraction of image features is a crucial step in many image analysis tasks. In feature extraction methods Gaussian derivative kernels are frequently utilized. Blurring of the image due to convolution with these kernels gives rise to feature measures different from the intended value in the original image. We propose to solve this problem by explicitly modeling the scale dependency of derivatives combined with measurement of derivatives at multiple scales. This approach is illustrated in methods for feature measurement in curvilinear structures. Results in 3D Confocal Images confirm that modelling of scale behavior of derivatives results in improved methods for center line localization in curved line structures and enables curvature and diameter measurement.