Authors:
Ernst D. Dickmanns
and
Hans-Joachim Wuensche
Affiliation:
Institut fuer Systemdynamik und Flugmechanik, Germany
Keyword(s):
Image features, edge detection, corner detection, shading models.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Feature Extraction
;
Features Extraction
;
Human-Computer Interaction
;
Image and Video Analysis
;
Informatics in Control, Automation and Robotics
;
Methodologies and Methods
;
Motion and Tracking
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Physiological Computing Systems
;
Segmentation and Grouping
;
Signal Processing, Sensors, Systems Modeling and Control
;
Software Engineering
;
Video Analysis
Abstract:
A stripe-based image evaluation scheme for real-time vision has been developed allowing efficient detection of the following classes of features: 1. ‘Nonplanarity’ feature for separating image regions treatable by planar shading models from the rest containing textured regions and corners; 2. edges and 3. smoothly shaded regions between edges, and 4. corners for stable 2-D feature tracking. All these features are detected by evaluating receptive fields (masks) with four mask elements shifted through stripes, both in row and column direction. Efficiency stems from re-use of intermediate results in mask elements in neighboring stripes and from coordinated use of these results in different feature extractors. Corner detection with compute-intensive algorithms can be confined to a small (but highly likely) fraction of the images exploiting the efficient nonplanarity feature. Application to road scenes is discussed.