Theory and experiment of Fourier–Bessel field calculation and tuning of a pulsed wave annular array

Fox, P.D.; Cheng, Jiqi; Liu, Jianyu

doi:10.1121/1.1560211

Cited by 13 publications

(10 citation statements)

References 33 publications

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“…FMT and its derivation [22] have been extensively used for object recognition [23][24] and invariant watermarking [25] . The spatial log-polar transformation, in which a Cartesian image was resampled as a logarithmic function of the distance from the center, was first proposed by Schwartz [26] , and then applied to feature-detection [27] and face-recognition [28] . Another polar frequency feature based on the Fourier-Bessel transform (FBT) was exploited for face recognition [29] .…”

Section: Related Workmentioning

confidence: 99%

PM-DFT: A New Local Invariant Descriptor Towards Image Copy Detection

Ling

Wang

Yan

et al. 2011

J. Comput. Sci. Technol.

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Currently, global-features-based image copy detection is vulnerable to geometric transformations like cropping, shift, and rotations. To resolve this problem, some algorithms based on local descriptors have been proposed. However, the local descriptors, which were originally designed for object recognition, are not suitable for copy detection because they cause the problems of false positives and ambiguities. Instead of relying on the local gradient statistic as many existing descriptors do, we propose a new invariant local descriptor based on local polar-mapping and discrete Fourier transform. Then based on this descriptor, we propose a new framework of copy detection, in which virtual prior attacks and attack weight are employed for training and selecting only a few robust features. This consequently improves the storage and detection efficiency. In addition, it is worth noting that the feature matching takes the locations and orientations of interest points into consideration, which increases the number of matched regions and improves the recall. Experimental results show that the new descriptor is more robust and distinctive, and the proposed copy detection scheme using this descriptor can substantially enhance the accuracy and recall of copy detection and lower the false positives and ambiguities.

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Section: Related Workmentioning

confidence: 99%

PM-DFT: A New Local Invariant Descriptor Towards Image Copy Detection

Ling

Wang

Yan

et al. 2011

J. Comput. Sci. Technol.

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“…The Fourier-Bessel (FB) series [19,20] found several applications in analyzing patterns in a circular domain [20,21] and is useful to describe the radial and angular components in images. Let f(x,y) be the region of interest in the image.…”

Section: Polar Frequency Analysismentioning

confidence: 99%

Local approach for face verification in polar frequency domain

Zana¹,

César²,

Feris³

et al. 2006

Image and Vision Computing

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“…An alternative representation of an image in the polar frequency domain is the two-dimensional Fourier-Bessel Transform [Bowman 1958;Rosental et al 1982]. This transform found several applications in analyzing patterns in a circular domain [Zwick and Zeitler 1973;Guan, et al 2001;Fox et al 2003], but was seldom exploited for image recognition. One of such rare examples is the work of Cabrera et al [1992], who applied the FBT to create descriptors of contour segments from images.…”

Section: Spatial Analysis In Polar Coordinatesmentioning

confidence: 99%

Face recognition based on polar frequency features

Zana

César

2006

ACM Trans. Appl. Percept.

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A novel biologically motivated face recognition algorithm based on polar frequency is presented. Polar frequency descriptors are extracted from face images by Fourier-Bessel transform (FBT). Next, the Euclidean distance between all images is computed and each image is now represented by its dissimilarity to the other images. A Pseudo-Fisher Linear Discriminant was built on this dissimilarity space. The performance of Discrete Fourier transform (DFT) descriptors, and a combination of both feature types was also evaluated. The algorithms were tested on a 40-and 1196-subjects face database (ORL and FERET, respectively). With 5 images per subject in the training and test datasets, error rate on the ORL database was 3.8, 1.25 and 0.2% for the FBT, DFT, and the combined classifier, respectively, as compared to 2.6% achieved by the best previous algorithm. The most informative polar frequency features were concentrated at low-to-medium angular frequencies coupled to low radial frequencies. On the FERET database, where an affine normalization preprocessing was applied, the FBT algorithm outperformed only the PCA in a rank recognition test. However, it achieved performance comparable to state-of-the-art methods when evaluated by verification tests. These results indicate the high informative value of the polar frequency content of face images in relation to recognition and verification tasks, and that the Cartesian frequency content can complement information about the subjects' identity, but possibly only when the images are not pre-normalized. Possible implications for human face recognition are discussed.

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Theory and experiment of Fourier–Bessel field calculation and tuning of a pulsed wave annular array

Cited by 13 publications

References 33 publications

PM-DFT: A New Local Invariant Descriptor Towards Image Copy Detection

PM-DFT: A New Local Invariant Descriptor Towards Image Copy Detection

Local approach for face verification in polar frequency domain

Face recognition based on polar frequency features

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