A dyadic wavelet affine invariant function for 2D shape recognition

Khalil, Mahmoud; Bayoumi, M.M.

doi:10.1109/34.954605

Cited by 82 publications

(77 citation statements)

References 25 publications

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“…4. These models have also been used in [3] to test the discriminative power of the invariant function and its ability to capture small variations. Since scale transformations 2 /2.…”

Section: Resultsmentioning

confidence: 99%

“…Fourier analysis and wavelet decomposition are two well-studied examples [3], [4], [5]. In these cases, the bases, used for boundary analysis, are mathematically well-defined to serve some specific analysis tasks.…”

Section: An Affine Invariant Function Using Pca Basesmentioning

confidence: 99%

“…These signals are then used to construct affine invariant functions. The choice of the signals, the decomposition levels and the wavelet functions used, have all resulted in a number of different approaches [1], [2], [3], [4], [5].…”

Section: Introductionmentioning

confidence: 99%

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An Affine Invariant Function using PCA Bases with an Application to Within-Class Object Recognition

Tzimiropoulos

Mitianoudis

Stathaki

2007

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07

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The problem of shape-based recognition of objects under affine transformations is considered. We focus on the construction of a robust and highly discriminative affine invariant function that can be used for within-class object recognition applications. Using the boundaries of the objects of interest, a training scheme, based on Principal Component Analysis (PCA), is proposed to derive a set of basis functions with desired properties. The derived bases are then used for the construction of a novel affine invariant function. The proposed invariant function is evaluated for the problem of aircraft silhouette identification and appears to achieve comparable performance to a popular wavelet-based affine invariant function. At the same time, the proposed framework is much simpler than that based on wavelet analysis.

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“…4. These models have also been used in [3] to test the discriminative power of the invariant function and its ability to capture small variations. Since scale transformations 2 /2.…”

Section: Resultsmentioning

confidence: 99%

Section: An Affine Invariant Function Using Pca Basesmentioning

confidence: 99%

See 1 more Smart Citation

An Affine Invariant Function using PCA Bases with an Application to Within-Class Object Recognition

Tzimiropoulos

Mitianoudis

Stathaki

2007

2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07

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“…Others methods to obtain the affine invariant can also be use as those proposed as in (Tieng and Boles, 1997b) and (Khalil and Bayoumi, 2001). Let's assume that the contourΓ(x i ,ỹ i ) is the affine transform of a given contour Γ(x i , y i ), ie.…”

Section: The Affine Invariantmentioning

confidence: 99%

“…2D shape recognition under affine transform uses generally two types of parameters as detailed in (Khalil and Bayoumi, 2001), (Khalil and Bayoumi, 2002) and (Tieng and Boles, 1997b): The parameterization by the affine length and by the enclosed area. The first type needs the derivative of high order and then are very sensitive to quantization and to noise.…”

Section: Parameterizationmentioning

confidence: 99%

Wavelet Transform for Partial Shape Recognition Using Sub-Matrix Matching

Zahzah

2008

Proceedings of the Third International Conference on Computer Vision Theory and Applications

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Abstract:In this paper, we propose a method for 2D partial shape recognition under affine transform using the discrete dyadic wavelet transform invariant to translation well known as Stationary Wavelet Transform or SWT. The method we propose here is about partial shape matching and is based firstly on contour representation using the wavelet transform. A technique of sub matrix matching is then used to match partial shapes. The representation is based on three steps, the contour is first parameterized by enclosed area, the affine invariant feature is then calculated to finally determine the natural axis which enable to fix the starting point. The knowledge of the orientation of the natural axis enables to adjust the starting point on the contour between the query and the models in a given database. Furthermore, the method can selects a subset of useful invariant features for the matching step. A sub-matrix matching algorithm developed by (Saber et al., 2005)is then used to determine correspondences for evaluation of partial similarity between an example template and a candidate object region. The method is tested on a database of 5000 fish species, and the results are very satisfactory.

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