A computational approach for corner and vertex detection
International Journal of Computer Vision
SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
Analysis of gray level corner detection
Pattern Recognition Letters
Gaussian Scale-Space Theory
Corner Detection in Color Images by Multiscale Combination of End-Stopped Cortical Cells
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
Comparing and Evaluating Interest Points
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)
Object detection in multi-channel and multi-scale images based on the structural tensor
CAIP'05 Proceedings of the 11th international conference on Computer Analysis of Images and Patterns
Anisotropic feature extraction from endoluminal images for detection of intestinal contractions
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
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Detection of low-level image features such as edges or corners has been an essential task of image processing for many years. Similarly, detectors of such image features constitute basic building blocks of almost every image processing system. However, today's growing amount of vision applications requires at least twofold research directions: search for detectors that work better than the other, at least for a chosen group of images of interest, and - at the other hand - search for new image features, such as textons or oriented structures of local neighborhoods of pixels. In this paper we present a new approach to the old problem of corner detection, as well as detection of areas in images that can be characterized by the same angular orientation. Both detecting techniques are based on a scale-space tensor representation of local structures, and present computationally attractive image feature detectors.