A nonlinear edge detection technique

Rosenfeld, A.

doi:10.1109/proc.1970.7756

Cited by 98 publications

(29 citation statements)

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“…The products of coefficients across scales are frequently used for image analysis. Witkin [20] provided the foundation for scale space theory by generalizing Rosenfeld's work [22], in which smoothing filters at dyadic scales are used. Based essentially on forming multiscale products of smoothed gradient estimates, this approach attempts to enhance the peaks of the gradients caused by true edges, while suppressing false peaks due to noise.…”

Section: Goi and Gci Detection By Multiscale Productsmentioning

confidence: 99%

Electroglottographic Measures Based on GCI and GOI Detection Using Multiscale Product

Bouzid¹,

Ellouze²

2008

INT J COMPUT COMMUN

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This paper deals with glottal parameter estimation such as local pitch and open quotient from electroglottographic signal (EGG). This estimation is based on glottal closing instants and glottal opening instants determined by a multi-scale product of this signal. Wavelet transform of EGG signal is made with a quadratic spline function. Wavelet coefficients calculated on different dyadic scales, show modulus maxima at localized discontinuities of EGG signal. The detected maxima and minima correspond to the glottal opening and closing instants called GOIs and GCIs. To improve the estimate precision, we operate the multi-scale product of wavelet transform coefficients of three successive dyadic scales. This processing enhances edge detection. A Multi-scale product is a nonlinear combination of successive scales; it reduces noise and spurious peaks. We apply cubic root amplitude on the product to improve the representation of weak amplitudes. The method has a good representation of GCI and a best detection of GOI. The method was tested on the Keele University database; it is effective and robust in multiple cases even for a typical signal showing undetermined GOIs and multiple peaks at GCIs. Finally precise measurement of these instants allows accurate estimation of prosodic parameters as local pitch and open quotient.

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Section: Goi and Gci Detection By Multiscale Productsmentioning

confidence: 99%

Electroglottographic Measures Based on GCI and GOI Detection Using Multiscale Product

Bouzid¹,

Ellouze²

2008

INT J COMPUT COMMUN

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“…Working before the advent of the wavelet framework, Rosenfeld and coworkers suggested forming multiscale point-wise products [26][27][28]. This is intended to enhance multiscale peaks due to edges, while suppressing noise, Figure 1.…”

Section: Multiscale Productsmentioning

confidence: 99%

“…The SNR input-output relationship is plotted in figure 6, for K = 2 and K = 3, using equations (22) and (26). The line SNR i = SNR o is shown for reference.…”

Section: Step and Pulse Responsementioning

confidence: 99%

“…We also note the earlier work of Witkin [33], who developed ideas for multiscale characterization of signals. Working on image processing before the advent of wavelets, Rosenfeld and coworkers suggested an interesting idea, to form multiscale point-wise products [26][27][28]. This approach is intended to enhance multiscale peaks due to edges, while suppressing noise, by exploiting the multiscale correlation due to the presence of the desired signal in a direct (albeit nonlinear) way.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Wavelet Transform Multiscale Products for Step Detection and Estimation

Sadler¹,

Swami²

1998

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We consider discrete wavelet transform (DWT) multiscale products for detection and estimation of steps. Here the DWT is an overcomplete approximation to smoothed gradient estimation, with smoothing varied over dyadic scale, as developed by Mallat and Zhong. We show that the multiscale product approach, as first proposed by Rosenfeld for edge detection, is a nonlinear whitening transformation. We characterize the resulting non-Gaussian heavy-tailed densities. The results may be applied to edge detection with a false alarm constraint. The response to impulses, steps, and pulses is also characterized. A general closed-form expression for the Cramer-Rao bound (CRB) for discrete and continuous-time step-change location estimation in independent identically distributed non-Gaussian noise is developed, generalizing previous results. We consider location estimation using multiscale products, and compare results to the appropriate CRB.ii

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“…However, we have observed that the absolute magnitudes of the gradient are not as relevant to our analysis as their relative magnitudes: Boundaries can be adequately characterized as the local maxima of the gradient (Rosenfeld 1970;Haralick 1984;Canny 1986) and give equal weight to equally good edge candidates regardless of their gradient strengths.…”

Section: Edge Modelmentioning

confidence: 99%

An optimization framework for feature extraction

Fua

Hanson

1991

Machine Vis. Apps.

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Abstract:In this paper, we propose a unified optimization framework for feature extraction that lets us simultaneously take into account image data and semantic knowledge: We model objects using a language that specifies both photometric and geometric constraints and defines an information-theoretic objective function that measures the fit of the models to the data. We then treat the problem of finding objects as one of generating the optimal description of the image in terms of this language.We have validated our framework by performing extensive experiments on detecting objects in aerial imagery described by simple geometric constraints and have developed two algorithms for generating optimal descriptions. The first one starts with a rough sketch of a polygonal object and deforms the initial contour to maximize the objective function, thus finding object outlines. The second one automatically extracts complex rectilinear buildings from complex aerial images.

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A nonlinear edge detection technique

Cited by 98 publications

References 0 publications

Electroglottographic Measures Based on GCI and GOI Detection Using Multiscale Product

Electroglottographic Measures Based on GCI and GOI Detection Using Multiscale Product

Analysis of Wavelet Transform Multiscale Products for Step Detection and Estimation

An optimization framework for feature extraction

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