Journal
PATTERN RECOGNITION
Volume 41, Issue 4, Pages 1268-1279Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.patcog.2007.09.006
Keywords
curve detection; randomized Hough transform; Hough transform; image processing; ellipse; ultrasound; fetal head
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An iterative randomized Hough transform (IRHT) is developed for detection of incomplete ellipses in images with strong noise. The IRHT iteratively applies the randomized Hough transform (RHT) to a region of interest in the image space. The region of interest is determined from the latest estimation of ellipse parameters. The IRHT zooms in on the target curve by iterative parameter adjustments and reciprocating use of the image and parameter spaces. During the iteration process, noise pixels are gradually excluded from the region of interest, and the estimation becomes progressively close to the target. The IRHT retains the advantages of RHT of high parameter resolution, computational simplicity and small storage while overcoming the noise susceptibility of RHT. Indivisible, multiple instances of ellipse can be sequentially detected. The IRHT was first tested for ellipse detection with synthesized images. It was then applied to fetal head detection in medical ultrasound images. The results demonstrate that the IRHT is a robust and efficient ellipse detection method for real-world applications. (c) 2007 Elsevier Ltd. All rights reserved.
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