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Issue No.11 - November (1994 vol.16)
pp: 1057-1073
ABSTRACT
<p>An analogy is made between each straight line in an image and a planar propagating wavefront impinging on an array of sensors so as to obtain a mathematical model exploited in recent high resolution methods for direction-of-arrival estimation in sensor array processing. The new so-called SLIDE (subspace-based line detection) algorithm then exploits the spatial coherence between the contributions of each line in different rows of the image to enhance and distinguish a signal subspace that is defined by the desired line parameters. SLIDE yields closed-form and high resolution estimates for line parameters, and its computational complexity and storage requirements are far less than those of the standard method of the Hough transform. If unknown a priori, the number of lines is also estimated in the proposed technique. The signal representation employed in this formulation is also generalized to handle grey-scale images as well. The technique has also been generalized to fitting planes in 3-D images. Some practical issues of the proposed technique are given.</p>
INDEX TERMS
edge detection; object recognition; array signal processing; computational complexity; curve fitting; parameter estimation; SLIDE; subspace-based line detection; direction-of-arrival estimation; sensor array processing; straight lines; line parameter estimation; computational complexity; Hough transform; signal representation; grey-scale images; 3D images
CITATION
H.K. Aghajan, T. Kailath, "SLIDE: Subspace-Based Line Detection", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.16, no. 11, pp. 1057-1073, November 1994, doi:10.1109/34.334386
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