Heterogeneous image feature integration via multi-modal spectral clustering

A fully automated reconstruction of the trajectory of image sequences using point correspondences is turning into a routine practice. However, there are cases in which point features are hardly detectable, cannot be localized in a stable distribution, and consequently lead to an insufficient pose estimation. This paper presents a triplet-wise scheme for calibrated relative pose estimation from image point and line triplets, and investigates the effectiveness of the feature integration upon the relative pose estimation. To this end, we employ an existing point matching technique and propose a method for line triplet matching in which the relative poses are resolved during the matching procedure. The line matching method aims at establishing hypotheses about potential minimal line matches that can be used for determining the parameters of relative orientation (pose estimation) of two images with respect to the reference one; then, quantifying the agreement using the estimated orientation parameters. Rather than randomly choosing the line candidates in the matching process, we generate an associated lookup table to guide the selection of potential line matches. In addition, we integrate the homologous point and line triplets into a common adjustment procedure. In order to be able to also work with image sequences the adjustment is formulated in an incremental manner. The proposed scheme is evaluated with both synthetic and real datasets, demonstrating its satisfactory performance and revealing the effectiveness of image feature integration.

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QR image feature extraction effectiveness based on metrics using spectral clustering and grey level Co-Occurrence matrix algorithm

Materials Today Proceedings ◽

10.1016/j.matpr.2020.06.551 ◽

2020 ◽

Vol 33 ◽

pp. 4112-4116

Author(s):

R. Sandha ◽

N. Kirubanandasarathy

Keyword(s):

Feature Extraction ◽

Spectral Clustering ◽

Image Feature ◽

Grey Level ◽

Image Feature Extraction ◽

Matrix Algorithm ◽

Occurrence Matrix

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High-resolution electron microscopy of the atomic structure of some grain boundaries in Au

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100143663 ◽

1986 ◽

Vol 44 ◽

pp. 414-415

Author(s):

W. Krakow ◽

D. A. Smith

Keyword(s):

Atomic Structure ◽

High Resolution Electron Microscopy ◽

Image Features ◽

Image Feature ◽

Resolution Electron ◽

Tilt Boundaries ◽

Processing Techniques ◽

Atom Position ◽

Structure Configuration

The successful determination of the atomic structure of [110] tilt boundaries in Au stems from the investigation of microscope performance at intermediate accelerating voltages (200 and 400kV) as well as a detailed understanding of how grain boundary image features depend on dynamical diffraction processes variation with specimen and beam orientations. This success is also facilitated by improving image quality by digital image processing techniques to the point where a structure image is obtained and each atom position is represented by a resolved image feature. Figure 1 shows an example of a low angle (∼10°) Σ = 129/[110] tilt boundary in a ∼250Å Au film, taken under tilted beam brightfield imaging conditions, to illustrate the steps necessary to obtain the atomic structure configuration from the image. The original image of Fig. 1a shows the regular arrangement of strain-field images associated with the cores of ½ [10] primary dislocations which are separated by ∼15Å.

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