Lateral histograms for efficient object location: Speed versus ambiguity
Pattern Recognition Letters
A high speed algorithm for circular object location
Pattern Recognition Letters
A modified Hough scheme for general circle location
Pattern Recognition Letters
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A sampling approach to ultra-fast object location
Real-Time Imaging
Machine Vision: Theory, Algorithms, Practicalities
Machine Vision: Theory, Algorithms, Practicalities
IEEE Transactions on Computers
Local Detection Of Defects From Image Sequences
International Journal of Applied Mathematics and Computer Science - Issues in Fault Diagnosis and Fault Tolerant Control
Multidimensional Systems and Signal Processing
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This paper has developed a generalised sampling strategy for the rapid location of objects in digital images. In this strategy a priori information on the possible locations of objects is used to guide the sampling process, and earlier body-based and edge-based approaches emerge automatically on applying the right a priori probability maps. In addition, the limitations of the earlier regular sampling technique have been clarified and eased-with the result that sampling patterns are better matched to the positions of the image boundaries. These methods lead to improved speeds of operation both in the cases where all the objects in an image have to be located and also where the positions of individual objects have to be updated. Finally, the method is interesting in being intrinsically able to perform full binary search tree edge location without the need for explicit programming.