Perimeter estimation based on grey level object representation

• We present a novel method that provides an accurate and precise estimate of the length of the boundary (perimeter) of an object, by taking into account gray-levels on the boundary of the digitization of the same object. Assuming a model where pixel intensity is proportional to the coverage of a pixel, we show that the presented method provides error-free measurements of the length of straight boundary segments in the case of non-quantized pixel values. For a more realistic situation, where pixel values are quantized, we derive optimal estimates that minimize the maximal estimation error. We show that the estimate converges toward a correct value as the number of gray-levels tends toward infinity. The method is easy to implement; we provide complete pseudo-code. Since the method utilizes only a small neighborhood, it is very easy to parallelize. We evaluate the estimator on a set of concave and convex shapes with known perimeters, digitized at increasing resolution.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)

Nyckelord

Image analysis

Bildanalys

Computerized Image Analysis

Datoriserad bildanalys

Publikations- och innehållstyp

vet (ämneskategori)

rap (ämneskategori)