Fast computation of pseudo Zernike moments

Al-Rawi, Mohammed

doi:10.1007/s11554-009-0118-0

Cited by 27 publications

(7 citation statements)

References 16 publications

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“…A p-recursive method focusing on reducing time complexity through the fast computing of the pseudo-Zernike radial polynomials using a hybrid method was presented by the authors of [30], where:…”

Section: Pseudo-zernike Moments-pzmsmentioning

confidence: 99%

Application of a Novel Automatic Method for Determining the Bilateral Symmetry Midline of the Facial Skeleton Based on Invariant Moments

Silva

Jenkyn

2020

Symmetry

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Assuming a symmetric pattern plays a fundamental role in the diagnosis and surgical treatment of facial asymmetry, for reconstructive craniofacial surgery, knowing the precise location of the facial midline is important since for most reconstructive procedures the intact side of the face serves as a template for the malformed side. However, the location of the midline is still a subjective procedure, despite its importance. This study aimed to automatically locate the bilateral symmetry midline of the facial skeleton based on an invariant moment technique using pseudo-Zernike moments. A total of 367 skull images were evaluated using the proposed technique. The technique was found to be reliable and provided good accuracy in the symmetry planes. This new technique will be utilized for subsequent studies to evaluate diverse craniofacial reconstruction techniques.

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Section: Pseudo-zernike Moments-pzmsmentioning

confidence: 99%

Application of a Novel Automatic Method for Determining the Bilateral Symmetry Midline of the Facial Skeleton Based on Invariant Moments

Silva

Jenkyn

2020

Symmetry

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“…Then, the shape is described by features extracted from the whole image [14]. Most commonly used methods as form descriptors are moments invariant like Hu [15], Zernike moments [16] and Pseudo Zernike Moments [17].…”

Section: Work Relatedmentioning

confidence: 99%

Plants Leaves Images Segmentation Based on Pseudo Zernike Moments

Behloul¹,

Belkacemi²

2015

IJIGSP

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Leaves images segmentation is an important task in the automated plant identification. Images leaf segmentation is the process of extracting the leaf from its background, which is a challenging task. In this paper, we propose an efficient and effective new approach for leaf image segmentation, we aim to separate the leaves from the background and from their shadow generated when the photo was taken. The proposed approach calculates the local descriptors for the image that will be classified for the separation of the different image's region. We use Pseudo Zernike Moments (PZM) as a local descriptor combined with K-means algorithm for clustering. The efficient of PZM for features extraction lead to very good results in very short time. The validation tests applied on a variety of images, showed the ability of the proposed approach for segmenting effectively the image. The results demonstrate a real improvement compared to those of new existing segmentation method.

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“…where y r is the r th digital filter output and C p,r is a matrix of coefficients directly obtained from the impulse responses of the all-pole digital filters as given in [27]:…”

Section: Hatamian's Modelmentioning

confidence: 99%