Object recognition using shape-from-shading

This paper investigates whether surface topography information extracted from intensity images using a recently reported shape-from-shading (SFS) algorithm can be used for the purposes of 3D object recognition. We consider how curvature and shape-index information delivered by this algorithm can be used to recognize objects based on their surface topography. We explore two contrasting object recognition strategies. The first of these is based on a low-level attribute summary and uses histograms of curvature and orientation measurements. The second approach is based on the structural arrangement of constant shape-index maximal patches and their associated region attributes. We show that region curvedness and a string ordering of the regions according to size provides recognition accuracy of about 96 percent. By polling various recognition schemes. including a graph matching method. we show that a recognition rate of 98-99 percent is achievable

Sub-wavelength surface IR imaging of soft-condensed matter

Outlined here is a technique for sub-wavelength infrared surface imaging performed using a phase matched optical parametric oscillator laser and an atomic force microscope as the detection mechanism. The technique uses a novel surface excitation illumination approach to perform simultaneously chemical mapping and AFM topography imaging with an image resolution of 200 nm. This method was demonstrated by imaging polystyrene micro-structures

C58 on Au(111): a scanning tunneling microscopy study

C58 fullerenes were adsorbed onto room temperature Au(111) surface by low-energy (~6 eV) cluster ion beam deposition under ultrahigh vacuum conditions. The topographic and electronic properties of the deposits were monitored by means of scanning tunnelling microscopy (STM at 4.2 K). Topographic images reveal that at low coverages fullerene cages are pinned by point dislocation defects on the herringbone reconstructed gold terraces (as well as by step edges). At intermediate coverages, pinned monomers, act as nucleation centres for the formation of oligomeric C58 chains and 2D islands. At the largest coverages studied, the surface becomes covered by 3D interlinked C58 cages. STM topographic images of pinned single adsorbates are essentially featureless. The corresponding local densities of states are consistent with strong cage-substrate interactions. Topographic images of [C58]n oligomers show a stripe-like intensity pattern oriented perpendicular to the axis connecting the cage centers. This striped pattern becomes even more pronounced in maps of the local density of states. As supported by density functional theory, DFT calculations, and also by analogous STM images previously obtained for C60 polymers (M. Nakaya et al., J. Nanosci. Nanotechnol. 11, 2829 (2011)), we conclude that these striped orbital patterns are a fingerprint of covalent intercage bonds. For thick C58 films we have derived a band gap of 1.2 eV from scanning tunnelling spectroscopy data, STS, confirming that the outermost C58 layer behaves as a wide band semiconductor

Surface Roughness Gradients Reveal Topography‐Specific Mechanosensitive Responses in Human Mesenchymal Stem Cells

The topographic features of an implant, which mechanically regulate cell behaviors and functions, are critical for the clinical success in tissue regeneration. How cells sense and respond to the topographical cues, e.g., interfacial roughness, is yet to be fully understood and even debatable. Here, the mechanotransduction and fate determination of human mesenchymal stem cells (MSCs) on surface roughness gradients are systematically studied. The broad range of topographical scales and high‐throughput imaging is achieved based on a catecholic polyglycerol coating fabricated by a one‐step‐tilted dip‐coating approach. It is revealed that the adhesion of MSCs is biphasically regulated by interfacial roughness. The cell mechanotransduction is investigated from focal adhesion to transcriptional activity, which explains that cellular response to interfacial roughness undergoes a direct force‐dependent mechanism. Moreover, the optimized roughness for promoting cell fate specification is explored

Comparison of the accuracy of voxel based registration and surface based registration for 3D assessment of surgical change following orthognathic surgery

Purpose: Superimposition of two dimensional preoperative and postoperative facial images, including radiographs and photographs, are used to evaluate the surgical changes after orthognathic surgery. Recently, three dimensional (3D) imaging has been introduced allowing more accurate analysis of surgical changes. Surface based registration and voxel based registration are commonly used methods for 3D superimposition. The aim of this study was to evaluate and compare the accuracy of the two methods.<p></p> Materials and methods: Pre-operative and 6 months post-operative cone beam CT scan (CBCT) images of 31 patients were randomly selected from the orthognathic patient database at the Dental Hospital and School, University of Glasgow, UK. Voxel based registration was performed on the DICOM images (Digital Imaging Communication in Medicine) using Maxilim software (Medicim-Medical Image Computing, Belgium). Surface based registration was performed on the soft and hard tissue 3D models using VRMesh (VirtualGrid, Bellevue City, WA). The accuracy of the superimposition was evaluated by measuring the mean value of the absolute distance between the two 3D image surfaces. The results were statistically analysed using a paired Student t-test, ANOVA with post-hoc Duncan test, a one sample t-test and Pearson correlation coefficient test.<p></p> Results: The results showed no significant statistical difference between the two superimposition methods (p<0.05). However surface based registration showed a high variability in the mean distances between the corresponding surfaces compared to voxel based registration, especially for soft tissue. Within each method there was a significant difference between superimposition of the soft and hard tissue models.<p></p> Conclusions: There were no significant statistical differences between the two registration methods and it was unlikely to have any clinical significance. Voxel based registration was associated with less variability. Registering on the soft tissue in isolation from the hard tissue may not be a true reflection of the surgical change

Reconstituting ring-rafts in bud-mimicking topography of model membranes.

During vesicular trafficking and release of enveloped viruses, the budding and fission processes dynamically remodel the donor cell membrane in a protein- or a lipid-mediated manner. In all cases, in addition to the generation or relief of the curvature stress, the buds recruit specific lipids and proteins from the donor membrane through restricted diffusion for the development of a ring-type raft domain of closed topology. Here, by reconstituting the bud topography in a model membrane, we demonstrate the preferential localization of cholesterol- and sphingomyelin-enriched microdomains in the collar band of the bud-neck interfaced with the donor membrane. The geometrical approach to the recapitulation of the dynamic membrane reorganization, resulting from the local radii of curvatures from nanometre-to-micrometre scales, offers important clues for understanding the active roles of the bud topography in the sorting and migration machinery of key signalling proteins involved in membrane budding

Terrain analysis using radar shape-from-shading

This paper develops a maximum a posteriori (MAP) probability estimation framework for shape-from-shading (SFS) from synthetic aperture radar (SAR) images. The aim is to use this method to reconstruct surface topography from a single radar image of relatively complex terrain. Our MAP framework makes explicit how the recovery of local surface orientation depends on the whereabouts of terrain edge features and the available radar reflectance information. To apply the resulting process to real world radar data, we require probabilistic models for the appearance of terrain features and the relationship between the orientation of surface normals and the radar reflectance. We show that the SAR data can be modeled using a Rayleigh-Bessel distribution and use this distribution to develop a maximum likelihood algorithm for detecting and labeling terrain edge features. Moreover, we show how robust statistics can be used to estimate the characteristic parameters of this distribution. We also develop an empirical model for the SAR reflectance function. Using the reflectance model, we perform Lambertian correction so that a conventional SFS algorithm can be applied to the radar data. The initial surface normal direction is constrained to point in the direction of the nearest ridge or ravine feature. Each surface normal must fall within a conical envelope whose axis is in the direction of the radar illuminant. The extent of the envelope depends on the corrected radar reflectance and the variance of the radar signal statistics. We explore various ways of smoothing the field of surface normals using robust statistics. Finally, we show how to reconstruct the terrain surface from the smoothed field of surface normal vectors. The proposed algorithm is applied to various SAR data sets containing relatively complex terrain structure