Marr–Hildreth algorithm

<p>In <a href="/facts/Computer_vision/Tl2Yyk66">computer vision</a>, the Marr–Hildreth algorithm is a method of <a href="/facts/Edge_detection/9VplpIcS">detecting edges</a> in <a href="/facts/Digital_image/3TNT47Mv">digital images</a>, that is, continuous curves where there are strong and rapid variations in image brightness. The Marr–Hildreth edge detection method is simple and operates by convolving the image with the <a href="/facts/Laplacian/kov9u3PT">Laplacian</a> of the <a href="/facts/Gaussian_function/5bG8Kpp9">Gaussian function</a>, or, as a fast approximation by <a href="/facts/Difference_of_Gaussians/VxgyK5xp">difference of Gaussians</a>. Then, <a href="/facts/Zero_crossing/g70XI9o6">zero crossings</a> are detected in the filtered result to obtain the edges. The Laplacian-of-Gaussian image operator is sometimes also referred to as the <a href="/facts/Mexican_hat_wavelet/JvEtddE5">Mexican hat wavelet</a> due to its visual shape when turned upside-down.  <a href="/facts/David_Marr_(psychologist)/mc7wyhYl">David Marr</a> and <a href="/facts/Ellen_Hildreth/rvqkvqJS">Ellen C. Hildreth</a> are two of the inventors.
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Marr–Hildreth algorithm open-in-new

Marr–Hildreth algorithm