The importance of rapid and accurate extraction of ellipses in images for model-based computer vision systems has long been recognised. The Hough transform technique has established itself as a robust method for shape extraction, however, its application to ellipses has been restricted by excessive computational and storage requirements. Direct extension of the Hough technique to ellipses is particularly demanding since a five-dimensional accumulator array is required. This paper presents a novel tristage technique for ellipse extraction based on decomposing the problem into sequentially executed stages. Candidate ellipse centres are determined using an improved centre-finding procedure and novel Hough-based procedures extract the remaining parameters in two further stages. Although multistage parameter extraction is not new, many of the problems that exist in previous schemes are resolved. In the new technique, the dimensionality of the accumulator arrays used does not exceed two, while their ranges are predefined. Memory savings are therefore significant. Concentric ellipses of the same orientation are shown to be extracted with little extra computational demand. Two extensions of the tristage technique to multiple ellipse extraction are presented and compared. When applied to real images, the new technique extracted multiple, concentric ellipses reliably and with reduced complexity.