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# Theory of edge detection

Image processing Canny edge detector Classification of discontinuities Political science Blob detection Computer vision Mathematics Computer science Linguistics Wavelet Quantum mechanics Intensity (physics) Politics Filter (signal processing) Epistemology Image (mathematics) Zero crossing Optics Physics Mathematical analysis Philosophy Artificial intelligence Composite material Enhanced Data Rates for GSM Evolution Gaussian Voltage Materials science Edge detection Law Range (aeronautics) Representation (politics) Scale (ratio) Simple (philosophy) Zero (linguistics)

David Marr,Ellen C. Hildreth

DOI：10.1098/rspb.1980.0020 PMID：6102765

A theory of edge detection is presented. The analysis proceeds in two parts. (1) Intensity changes, which occur in a natural image over a wide range of scales, are detected separately at different scales. An appropriate filter for this purpose at a given scale is found to be the second derivative of a Gaussian, and it is shown that, provided some simple conditions are satisfied, these primary filters need not be orientation-dependent. Thus, intensity changes at a given scale are best detected by finding the zero values of ∇ 2 G(x, y) * I(x, y) for image I, where G(x, y) is a two-dimen­sional Gaussian distribution and ∇ 2 is the Laplacian. The intensity changes thus discovered in each of the channels are then represented by oriented primitives called zero-crossing segments, and evidence is given that this representation is complete. (2) Intensity changes in images arise from surface discontinuities or from reflectance or illumination bound­aries, and these all have the property that they are spatially localized. Because of this, the zero-crossing segments from the different channels are not independent, and rules are deduced for combining them into a description of the image. This description is called the raw primal sketch. The theory explains several basic psychophysical findings, and the opera­tion of forming oriented zero-crossing segments from the output of centre-surround ∇ 2 G filters acting on the image forms the basis for a physiological model of simple cells (see Marr & Ullman 1979).

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