Author :
Paglieroni, David W. ; Ford, Gary E. ; Tsujimoto, Eric M.
Abstract :
A new search method over (x,y,θ), called position-orientation masking is introduced. It is applied to vertices that are allowed to be separated into different bands of acuteness. Position-orientation masking yields exactly one θ value for each (x,y) that it considers to be the location of a possible occurrence of an object. Detailed matching of edge segments is performed at only these candidate (x,y,θ) to determine if objects actually do occur there. Template matching is accelerated dramatically since the candidates comprise only a small fraction of all (x,y,θ). Position-orientation masking eliminates the need for exhaustive search when deriving the candidate (x,y,θ). Search is guided by correlations between template vertices and distance transforms of image vertices. When a poor correlation is encountered at a particular position and orientation, nearby positions at that orientation and nearby orientations at that position are masked out. Position and orientation traversal are by quadrant and binary decomposition
Keywords :
correlation methods; edge detection; search problems; transforms; binary decomposition; correlations; distance transforms; edge segments matching; image vertices; parametric search; position-orientation masking; quadrant decomposition; template matching; template vertices; Acceleration; Detectors; Image edge detection; Image segmentation; Instruments; Object detection; Pattern matching; Pixel; Search methods;