IEEE Transactions on Pattern Analysis and Machine Intelligence
Best Linear Unbiased Estimators for Properties of Digitized Straight Lines
IEEE Transactions on Pattern Analysis and Machine Intelligence
Algorithms for subpixel registration
Computer Vision, Graphics, and Image Processing
Estimation of a circular arc center and its radius
Computer Vision, Graphics, and Image Processing
Length estimators for digitized contours
Computer Vision, Graphics, and Image Processing
A geometric approach to subpixel registration accuracy
Computer Vision, Graphics, and Image Processing
Moment-preserving line detection
Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Number of Digital Straight Line Segments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Precision Edge Contrast and Orientation Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tree Searched Chain Coding for Subpixel Reconstruction of Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Topology of Locales and Its Effects on Position Uncertainty
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Achievable Accuracy in Edge Localization
IEEE Transactions on Pattern Analysis and Machine Intelligence
Subpixel Precision of Straight-Edged Shapes for Registration and Measurement
IEEE Transactions on Pattern Analysis and Machine Intelligence
Spatial Sampling of Printed Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Twenty Years of Document Image Analysis in PAMI
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digitized Circular Arcs: Characterization and Parameter Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of The Third Workshop on Analytics for Noisy Unstructured Text Data
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A basis for determining the best possible precision for the position of a given object in a digital image is developed. The approach is general, being independent of object-form and providing a performance bound on all position estimation schemes. The central concepts in the development are the locale and total variation of the image function. An easily computed bound for the smallest attainable RSM position estimation error is developed. The best possible estimate is given by the centroids of the locales. The analysis of geometric precision using locales shows how object position-uncertainty depends on the object's position. Visual inspection of the easily generated locale pattern gives a qualitative impression of the spatial distribution of geometric precision. The analytic techniques developed provide avenues for both qualitative and quantitative evaluation of target forms and position estimation schemes in terms of their precision mensuration capabilities.