An algorithm for automatic curve detection

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• 作者：Z. Martí ; nez^a ; ^{zmartinez@usb.ve} ; ^{wilxax42@gmail.com} ; ^{avalonia@cantv.net} ; C. Ludeñ ; a^b ; ^{cludena@ivic.gov.ve}
• 关键词：Curve detection ; Curve selection ; Models selection ; Directional energy ; Gabor’ ; s filters ; Contourlets ; Curvelets
• 刊名：Computational Statistics and Data Analysis
• 出版年：2011
• 出版时间：1 June 2011
• 年：2011
• 卷：55
• 期：6
• 页码：2158-2171
• 全文大小：1034 K

文摘

In this article we consider the problem of automatic detection of curves, as opposed to straight lines, over a noisy image. We develop a two step model selection procedure based on a contourlet expansion of the image and prove the method is consistent in probability. The first step is based on usual threshold methods for frames. The second step selects pixels that spread energy over several simultaneous directions which is a known property of curve-like figures. We apply the proposed method to synthetic images and show its capability to separate curves from a noisy background and from a random collection of small straight lines. A practical application to seismic grids is also considered.