Moment forms invariant to rotation and blur in arbitrary number of dimensions

Flusser, Jan; Boldyš, Jiří; Zitová, Barbara

doi:10.1109/tpami.2003.1177154

Cited by 97 publications

(35 citation statements)

References 36 publications

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“…Despite of this, the invariants have found successful applications in normalizing blurred images into canonical forms [27] , in template to scene matching of satellite images, in blurred digit and character recognition [28] , and in registration of images obtained by digital subtraction angiography [29] . Flusser et al [30] proposed a grouptheoretic approach to extend the combined invariant into 3D case. Zhang et al [31] exploited the combined blurrotation invariants.…”

Section: Combine Anti-blur With the New Invariantsmentioning

confidence: 99%

Illumination-robust and Anti-blur Feature Descriptors for Image Matching in Abdomen Reconstruction

Liu

Xiao

Tang

et al. 2014

Int. J. Autom. Comput.

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This paper puts forward a method for abdomen panorama reconstruction based on a stereo vision system. For the purpose of recovering the abdomen completely and accurately under the condition of actual photographing with illumination variance and blur noise, some innovative combined feature descriptors are presented on the basis of Hu-moment invariants. Furthermore, considering the study on the abdomen surface reconstruction, a circle template which is divided into 6 sectors is designed. It is noted that a descriptor merely using gray intensity is not able to provide sufficient information for feature description. Consequently, the sector entropy which denotes the structure characteristics is drawn into the feature descriptor. By means of the combined effect of the gray intensity and the sector entropy, the similarity measurement is conducted for the final abdomen reconstruction. The experimental results reveal that the proposed method can acquire a high precision of abdomen reconstruction similar to the 3D scanner. This stereo vision system has wide practicability in the field of clothing.

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Section: Combine Anti-blur With the New Invariantsmentioning

confidence: 99%

Illumination-robust and Anti-blur Feature Descriptors for Image Matching in Abdomen Reconstruction

Liu

Xiao

Tang

et al. 2014

Int. J. Autom. Comput.

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“…Geometric moments have been previously utilized in medical image processing [20], [22] to construct invariants to similarity transformations, which can be used for automatic recognition of pathological deformations. Geometric moments are the basis for the computation of different kinds of moments, in particular Zernike moments.…”

Section: B 3-d Geometric Moment Invariantsmentioning

confidence: 99%

Morphological Characterization of Intracranial Aneurysms Using 3-D Moment Invariants

Millan

Dempere-Marco

Pozo

et al. 2007

IEEE Trans. Med. Imaging

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Abstract-Rupture of intracranial saccular aneurysms is the most common cause of spontaneous subarachnoid hemorrhage, which has significant morbidity and mortality. Although there is still controversy regarding the decision on which unruptured aneurysms should be treated, this is based primarily on their size. Nonetheless, many large lesions do not rupture whereas some small ones do. It is commonly accepted that hemodynamical factors are important to better understand the natural history of cerebral aneurysms. However, it might not always be practical to carry out a detailed computational analysis of such factors if a prompt assessment is required. Since shape is likely to be dependent on the balance between hemodynamic forces and the aneurysmal surrounding environment, an appropriate morphological 3-D characterization is likely to provide a practical surrogate to quickly evaluate the risk of rupture. In this paper, an efficient and novel methodology for 3-D shape characterization of cerebral aneurysms is described. The aneurysms are isolated by taking into account a portion of their adjacent vessels. Two methods to characterize the morphology of the aneurysms models using moment invariants have been considered: geometrical moment invariants (GMI) and Zernike moment invariants (ZMI). The results have been validated in a database containing 53 patients with a total of 31 ruptured aneurysms and 24 unruptured aneurysms. It has been found that ZMI indices are more robust than GMI, and seem to provide a reliable way to discriminate between ruptured and unruptured aneurysms. Correct rupture prediction rates of 80% were achieved in contrast to 66% that is found when the aspect ratio index is considered.

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“…However, Lo and Don [10] presented only 12 invariants of the second and third order of limited discriminability, without any generalization to higher orders, and they ignored completely the issue of symmetric objects. Their approach was later used in [11], where the additional invariance to blurring was introduced, and most recently in [12], where several higher-order invariants were presented but still without studying the impact of symmetry.…”

Section: Introductionmentioning

confidence: 99%

Recognition of Symmetric 3D Bodies

Suk

Flusser

2014

Symmetry

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The paper deals with the recognition of symmetric three-dimensional (3D) bodies that can be rotated and translated. We provide a complete list of all existing combinations of rotation and reflection symmetries in 3D. We define 3D complex moments by means of spherical harmonics, and the influence of individual symmetry groups on complex moment values is studied. Each particular symmetry pre-defines certain moment values. These moments can no longer differentiate between two objects of the same symmetry, which decreases the recognition power of the feature set. They should not be included when constructing the invariants. Translation and rotation invariants up to the fourth order are presented and their performance is studied on both artificial and real data.

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Moment forms invariant to rotation and blur in arbitrary number of dimensions

Cited by 97 publications

References 36 publications

Illumination-robust and Anti-blur Feature Descriptors for Image Matching in Abdomen Reconstruction

Illumination-robust and Anti-blur Feature Descriptors for Image Matching in Abdomen Reconstruction

Morphological Characterization of Intracranial Aneurysms Using 3-D Moment Invariants

Recognition of Symmetric 3D Bodies

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