A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Chamfer Matching: A Parametric Edge Matching Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of image registration techniques
ACM Computing Surveys (CSUR)
A framework for low level feature extraction
ECCV '94 Proceedings of the third European conference on Computer Vision (Vol. II)
Efficiently Locating Objects Using the Hausdorff Distance
International Journal of Computer Vision
An Unbiased Detector of Curvilinear Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic target recognition by matching oriented edge pixels
IEEE Transactions on Image Processing
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
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Novel similarity measures for object recognition and image matching are proposed, which are inherently robust against occlusion, clutter, and nonlinear illumination changes. They can be extended to be robust to global as well as local contrast reversals. The similarity measures are based on representing the model of the object to be found and the image in which the model should be found as a set of points and associated direction vectors. They are used in an object recognition system for industrial inspection that recognizes objects under Euclidean transformations in real time.