Feature matching based on geometric constraints in weakly calibrated stereo views of curved scenes

The identification of the correspondences of points of views is an important task. A new feature matching algorithm for weakly calibrated stereo images of curved scenes is proposed, based on mere geometric constraints. After initial correspondences are built via the epipolar constraint, many point-to-point image mappings called homographies are set up to predict the matching position for feature points. To refine the predictions and reject false correspondences, four schemes are proposed. Extensive experiments on simulated data as well as on real images of scenes of variant depths show that the proposed method is effective and robust.

Extraction of Geometric Features of Wear Particles in Color Ferr ograph Images Based on RGB Color Space

This paper analyzes the potential color f ormats of ferrograph images, and presents the algorithms of converting the forma ts to RGB(Red, Green, Blue) color space. Through statistical analysis of wear pa rticles′ geometric features of color ferrograph images in the RGB color space, we give the differences of ferrograph wear particles′ geometric features among RGB color spaces and gray scale space, and calculate their respective distributi ons.

Similarity-based denoising of point-sampled surfaces

A non-local denoising (NLD) algorithm for point-sampled surfaces (PSSs) is presented based on similarities, including geometry intensity and features of sample points. By using the trilateral filtering operator, the differential signal of each sample point is determined and called "geometry intensity". Based on covariance analysis, a regular grid of geometry intensity of a sample point is constructed, and the geometry-intensity similarity of two points is measured according to their grids. Based on mean shift clustering, the PSSs are clustered in terms of the local geometry-features similarity. The smoothed geometry intensity, i.e., offset distance, of the sample point is estimated according to the two similarities. Using the resulting intensity, the noise component from PSSs is finally removed by adjusting the position of each sample point along its own normal direction. Ex- perimental results demonstrate that the algorithm is robust and can produce a more accurate denoising result while having better feature preservation.

The effects of DS blade's geometry features on material's creep strength

Because of the better creep performance,the directional solidification(DS)Nickel-based turbine blades have been widely used in advanced aero-engines.However,the DS turbine blade's different abrupt geometrical changes at different regions cause a variation of temperature field at those regions.Subsequently,the variable temperature field is very likely to lead to a different grain structures at those different region,and those different grain structure finally give rise to a variation in material's creep performance at different region in DS turbine blade.To study the variation in creep strength among different regions of a DS turbine blade,this article designed and manufactured three types of DS specimens to simulate the geometry features of platform,shroud and body part of a typical DS turbine blade.Creep tests on these specimens were conducted under the stress level of 608 MPa and temperature of 850。C,the creep rupture life of platform-like and shroud-like specimens are 93%and 73%of body-like specimens'respectively,which support the assumption that there exists a certain variation in material's creep strength among different regions in DS turbine blades.The fracture positions of these specimens also support above conclusion.It is suggested that the material's creep strength variation among different locations of DS turbine blades should be considered in future turbine blade life design and prediction.

Geometric and amino acid type determinants for protein-protein interaction interfaces

Background： Protein-protein interactions are essential to many biological processes. The binding site information of protein-protein complexes is extremely useful to obtain their structures from biochemical experiments. Geometric description of protein structures is the precondition of protein binding site prediction and protein-protein interaction analysis. The previous description of protein surface residues is incomplete, and little attention are paid to the implication of residue types for binding site prediction. Methods： Here, we found three new geometric features to characterize protein surface residues which are very effective for protein-protein interface residue prediction. The new features and several commonly used descriptors were employed to train millions of residue type-nonspecific or specific protein binding site predictors. Results： The amino acid type-specific predictors are superior to the models without distinction of amino acid types. The performances of the best predictors are much better than those of the sophisticated methods developed before. Conclusions： The results demonstrate that the geometric properties and amino acid types are very likely to determine if a protein surface residue would become an interface one when the protein binds to its partner.

Three-Dimensional Volume Datafield Reconstruction from Physical Model

This paper focuses on entirety ioterpretation, representation and reconstruction of three-dimensional volume data sets based on the physical model of the data. The data model is represented by thIee-dimensional geometric model.The surfaces inside the datafield are extracted and matched to the model stirfaces in order to reconstruct the new datafield based on the model. A conclusion is drawn that physical modeling provides a good basis and approach to interpret and represellt the data sets. This paPer also presents a subdivision algorithm to fast traJce B-spline curve and the colltrary algorithm is adopted to extract the geometry feature of the curve.