Machine Perception of Linear Structure

Our approach is a departure from the procedures usually employed in the following important respects: (1) We recognize the typ ica l ly overlooked d is t inc t ion between lines and edges; f inding l ines offers s igni f icant simpl i f icat ions not available when searching for edges. (2) The perceptual pr imit ive we extract from the image to Indicate the local presence of l inear structure is a function of to ta l intensi ty var iat ion over an extended portion of the image rather than Intensity gradient Information which can be extracted with a mask-like " local image operator." While easy to compute, th is new pr imit ive appears to be more effect ive and stable than the almost universal ly employed gradient based pr imit ives. (3) The overal l procedure can be applied to an arb i t rary image with essential ly no human intervention (parameter tuning or attent ion focusing) and produces excellent resul ts . Examples of the delineation procedure are shown for ae r ia l , i ndus t r ia l , and radiographic imagery.