articleTop 10% cited
Seeded region growing
IEEE Transactions on Pattern Analysis and Machine Intelligence · 1994 · Vol. 16(6) · pp. 641–647
R. Adams✉(Commonwealth Scientific and Industrial Research Organisation)Leanne Bischof(Commonwealth Scientific and Industrial Research Organisation)
Abstract
We present here a new algorithm for segmentation of intensity images which is robust, rapid, and free of tuning parameters. The method, however, requires the input of a number of seeds, either individual pixels or regions, which will control the formation of regions into which the image will be segmented. In this correspondence, we present the algorithm, discuss briefly its properties, and suggest two ways in which it can be employed, namely, by using manual seed selection or by automated procedures.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Medical Image Segmentation TechniquesImage and Object Detection TechniquesCell Image Analysis TechniquesArtificial intelligencePixelComputer scienceImage segmentationSegmentationSelection (genetic algorithm)Pattern recognition (psychology)Computer visionImage (mathematics)
Citations
3,076
FWCI
10.70
field-weighted impact
References
16
Percentile
99%
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Citations per year
References
Watersheds in digital spaces: an efficient algorithm based on immersion simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence · 1991 · 5,517 citations
Image Analysis and Mathematical Morphology.
Biometrics · 1983 · 3,907 citations
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