Biomedical subjects

Alexander Kadyrov

Publications and source records attributed to Alexander Kadyrov.

4 recordsLinked to original sources

PubMed2006

Affine parameter estimation from the trace transform.

In this paper, we assume that we are given the images of two segmented objects, one of which may be an affinely distorted version of the other, and wish to recover the values of the parameters of the affine transformation between the two images. The images may also differ by the overall level of illumination. The multiplicative constant of such difference may also be recovered. We present a generic theoretical framework to solve this problem. In terms of this framework, other proposed methods may be interpreted. We show how, in this framework, one can recover the affine parameters in a way that is robust to various effects, such as occlusion and illumination variation. The proposed method is generic enough to be applicable also to matching two images that do not depict the same scene or object.

Algorithms↗

PubMed2006

The "invaders" algorithm: range of values modulation for accelerated correlation.

In this paper, we present an algorithm that allows the simultaneous calculation of several cross correlations. The algorithm works by shifting the range of values of different images/signals to occupy different orders of magnitude and then combining them to form a single composite image/signal. Because additional signals are placed in the space usually occupied by a single signal, we call this the "invaders algorithm," to imply that extra signals invade the space that normally belongs to a single signal. After correlation is performed, the individual results are recovered by performing the inverse operation. The limitations of the algorithm are imposed by the finite length of the mantissa of the hardware used, the precision of the algorithm that performs the cross correlation (e.g., the precision of the fast Fourier transform (FFT)) and by the actual values of the images/signals that are to be combined. The algorithm does not require any special hardware or special FFT algorithm. For typical 256 x 256 images, an acceleration by a factor of at least two in the calculation of their cross correlations is guaranteed using an ordinary PC or a laptop. As for smaller sized templates, tenfold accelerations may be achieved.

Algorithms↗

PubMed2005

Fast robust correlation.

A new, fast, statistically robust, exhaustive, translational image-matching technique is presented: fast robust correlation. Existing methods are either slow or non-robust, or rely on optimization. Fast robust correlation works by expressing a robust matching surface as a series of correlations. Speed is obtained by computing correlations in the frequency domain. Computational cost is analyzed and the method is shown to be fast. Speed is comparable to conventional correlation and, for large images, thousands of times faster than direct robust matching. Three experiments demonstrate the advantage of the technique over standard correlation.

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PubMed2004

Affine invariant features from the trace transform.

The trace transform is a generalization of the Radon transform that allows one to construct image features that are invariant to a chosen group of image transformations. In this paper, we propose a methodology and appropriate functionals that can be computed from the image function and which can be used to calculate features invariant to the group of affine transforms. We demonstrate the usefulness of the constructed image descriptors in retrieving images from an image database and compare it with relevant state-of-the-art object retrieval methods.

Algorithms↗