Superellipse Fitting for the Recovery and Classification of Mine-Like Shapes in Sidescan Sonar Images

Durá, Estrella; Bell, Judith; Lane, David M.

doi:10.1109/joe.2008.2002962

Cited by 30 publications

(19 citation statements)

References 29 publications

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“…In previous works [10]- [13], target classification algorithms using standard sidescan sonars are mainly based on the analysis of the shadows. With the arising of high resolution sonars, we expect a better resolution of the highlight of the target itself and more information should be contained in it.…”

Section: A What Precision Is Needed?mentioning

confidence: 99%

Real-time sidescan simulator and applications

et al. 2009

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New generations of sonars appeared in the last decade. The major interest in SAS systems and high frequency sonars is in the improvement of the sonar resolution and the reduction of noise level. Sonar images are distance-images but at high resolution they tends to appear visually as optical images. Usually the algorithms developed for sidescan were specific for sonar images due to the poor resolution essentially. With high resolution sonars, algorithms developed in the image processing field for natural images became applicable. In this paper we present a real-time and realistic sidescan simulator, and test image-based classification algorithms (such as PCA and eigenface algorithms) with synthetic images in order to characterize the precision necessary for these image-based algorithm to work.

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Section: A What Precision Is Needed?mentioning

confidence: 99%

Real-time sidescan simulator and applications

et al. 2009

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“…Shape feature Objects are also characterized by their shapes. Dura et al [16] showed that the shadows can be described by the active contour with different parameters. The computation cost of the parametric contour is very large on one hand, the vague boundary of ROI in the sonar images can be easily passed by the active contours.…”

Section: A Intensity Featurementioning

confidence: 99%

Forward-looking sonar image mosaicking by feature tracking

Song

Herrmann

Liu

et al. 2016

2016 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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Abstract-High-frequency forward-looking sonars are appropriate for the operation or search close to the seabed. Constructing a panoramic mosaic not only facilitates an interpretation of the underwater environment, but also supports the vehicle's self-localization. In this paper, a method to register sonar sequences is proposed that is based on the feature tracking using the particle filtering. Our methods starts with the extraction of the intensity, the texture and the shape features from the unstructured seabed environment. Next a region of interest (ROI) is tracked until it disappears from the view field of an autonomous unterwater vehicle (AUV). Then, another ROI is selected and the tracking procedures are repeated. Experimental results show that (1) Feature tracking is feasible for the forward-looking sonar image mosaicking. (2) Fusion of the texture and the shape feature lead to a robust feature extraction method for more precise motion estimation. (3) The prior information on the AUV's movement is necessary for the tracking of highlighted regions.

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“…It favors the detection of bright elliptical blobs that have the least amount of intensity variation, which is a typical feature of methods based on the Mumford-Shah framework; moreover, overlapping ellipses are avoided. In [19], a collection of salient contour points was extracted from sidescan sonar images to detect minelike shapes from their acoustic shadow; the six-parameter curves that best fit the data were Lamé curves, a family that includes ellipses. In a strategy that is the reverse of that found in [12], snakes were first applied in [20] to detect contours, and only then was an ellipse fitted to the snake.…”

Section: Previous Workmentioning

confidence: 99%

“…Finally, the overall gradient is given by summing the partial contributions found in (15), (16), (19), and (20).…”

Section: Optimizationmentioning

confidence: 99%

The Ovuscule

Thévenaz

Delgado-Gonzalo

Unser

2011

IEEE Trans. Pattern Anal. Mach. Intell.

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Abstract-We propose an active contour (a.k.a. snake) that takes the shape of an ellipse. Its evolution is driven by surface terms made of two contributions: the integral of the data over an inner ellipse, counterbalanced by the integral of the data over an outer elliptical shell. We iteratively adapt the active contour to maximize the contrast between the two domains, which results in a snake that seeks elliptical bright blobs. We provide analytic expressions for the gradient of the snake with respect to its defining parameters, which allows for the use of efficient optimizers. An important contribution here is the parameterization of the ellipse which we define in such a way that all parameters have equal importance; this creates a favorable landscape for the proceedings of the optimizer. We validate our construct with synthetic data and illustrate its use on real data as well.

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Superellipse Fitting for the Recovery and Classification of Mine-Like Shapes in Sidescan Sonar Images

Cited by 30 publications

References 29 publications

Real-time sidescan simulator and applications

Real-time sidescan simulator and applications

Forward-looking sonar image mosaicking by feature tracking

The Ovuscule

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