Geometric Shape Matching Research Articles

Analysis of the powder material and the structure of samples obtained from an aluminum alloy by selective laser melting

By selective laser melting, samples were synthesized from the powder material of the AlSi10Mg alloy. All samples are made of aluminum alloy metal powder. Granulometric analysis data and particle morphology were studied to determine the suitability of the powder used in the selective laser melting. To identify structural defects, the samples were polished from the end and from the side of the building platform. Using a metallographic microscope, the porosity of samples made at a flow rate from 7.28 * 105 to 2.23 * 106 was analyzed. The geometric shape matching of the initial three-dimensional model was analyzed using the holes in the samples as an example. The results of particle size analysis, sphericity of particles of powder material, as well as metallographic analysis of samples can be used to improve the performance of parts obtained from AlSi10Mg aluminum alloy by selective laser melting.

Approximating a planar convex set using a sparse grid

We show how to construct a set S of O(1/ε1.5) points such that for any convex set C contained in the unit square, the convex hull of the points in S that are contained in C has area at least |C|−ε. We present two algorithmic applications, for geometric shape matching and area approximation.

Elastic geometric shape matching for translations under the Manhattan norm

The term elastic geometric shape matching (EGSM) refers to geometric optimization problems that are a generalization of many classical and well-studied geometric shape matching problems. In a geometric shape matching problem, one seeks a single transformation that, if applied to a geometric object – the pattern – minimizes the distance of the transformed object to another geometric object – the model.In an EGSM problem, the pattern is partitioned into parts which are transformed by a collection of transformations, called a transformation ensemble, in order to minimize the distance of the individually transformed parts to the model under the constraint that specific pairs of transformations of the ensemble have to be similar. These constraints are defined by an abstract graph on the parts of the model, called the neighborhood graph.We present algorithms for an EGSM problem for point sets under translations where the neighborhood graph is a tree. We measure the similarity of the shapes by the L1-Hausdorff distance (and the Hausdorff distance induced by other polygonal metrics).

Study on the Algorithms of Vision Localization of IGBT Automatic Wire Equipment

In recent years, with the development of the science and technology, equipment automation has become a trend. IGBT(Insulated Gate Bipolar Transistor) automatic wire system is one of the key equipment, and the vision localization technology as the key technology for improving the performance, has become a key research area. This paper analyzes the principle of wire products, study template matching and geometric shape matching methods based on image processing technology. Experimental studies show that the vision positioning speed and the accuracy of the system has met the needs of wire equipment.

Dynamic Links Between Emerging Cognitive Skills and Brain Processes

The goal of the present study was to investigate whether advanced cognitive skills in one domain impact the neural processing of unrelated skills in a different cognitive domain. This question is related to the broader issue of how cognitive-neurodevelopment proceeds as different skills are mastered. To address this goal, event-related brain potentials (ERPs) were used to assess linkages between cognitive skills of preschool children as reflected in their performance on a pre-reading screening test (Get Ready To Read) and their neural responses while engaged in a geometric shape matching task. Sixteen children (10 males) participated in this study. The children ranged from 46 to 60 months (SD = 4.36 months). ERPs were recorded using a 128-electrode high-density array while children attended to presentations of matched and mismatched shapes (triangles, circles, or squares). ERPs indicated that children with more advanced pre-reading skills discriminated between matched and mismatched shapes earlier than children with poorer pre-readings skills. The earlier discrimination effect observed in the advanced group was localized over the occipital electrode sites whereas in the Low Group such effects were present over frontal, parietal, and occipital sites. Modeled magnetic resonance images (MRIs) of the ERP component sources identified differences in neural generators between the two groups. Both sets of findings support the hypothesis that processing in a poorer-performing group is more distributed temporally and spatially across the scalp, and reflects the engagement of more distributed brain regions. These findings are seen as support for a theory of neural-cognitive development that is advanced in the present article.

Cooperative Multitarget Tracking With Efficient Split and Merge Handling

For applications such as behavior recognition it is important to maintain the identity of multiple targets, while tracking them in the presence of splits and merges, or occlusion of the targets by background obstacles. Here we propose an algorithm to handle multiple splits and merges of objects based on dynamic programming and a new geometric shape matching measure. We then cooperatively combine Kalman filter-based motion and shape tracking with the efficient and novel geometric shape matching algorithm. The system is fully automatic and requires no manual input of any kind for initialization of tracking. The target track initialization problem is formulated as computation of shortest paths in a directed and attributed graph using Dijkstra's shortest path algorithm. This scheme correctly initializes multiple target tracks for tracking even in the presence of clutter and segmentation errors which may occur in detecting a target. We present results on a large number of real world image sequences, where upto 17 objects have been tracked simultaneously in real-time, despite clutter, splits, and merges in measurements of objects. The complete tracking system including segmentation of moving objects works at 25 Hz on 352times288 pixel color image sequences on a 2.8-GHz Pentium-4 workstation

Spatio-temporal patterns of neuronal activity: analysis of optical imaging data using geometric shape matching

Optical imaging of neuronal network activity yields information of spatial dynamics which generally is analyzed visually. The transient appearance of spatial activity patterns is difficult to gauge in a quantifiable manner, or may even altogether escape detection. Here, we employ geometric shape matching using Fréchet distances or straight skeletons to search for pre-selected patterns in optical imaging data with adjustable degrees of tolerance. Data were sampled from fluorescence changes of a voltage-sensitive dye recorded with a 464-photodiode array. Fluorescence was monitored in a neuronal network in vitro. Neuronal activity prompting fluorescence fluctuations consisted of spontaneous epileptiform discharges in neocortical slices from patients undergoing epilepsy surgery. The experiments show that: (a) spatial activity patterns can be detected in optical imaging data; (b) shapes such as ‘mini-foci’ appear in close correlation to bioelectric discharges monitored with field potential electrodes in a reproducible manner; (c) Fréchet distances yield more conservative matches regarding rectangular, and less conservative hits with respect to radially symmetric shapes than the straight skeleton approach; and (d) tolerances of 0.03–0.1 are suited to detect faithful images of pre-selected shapes, whereas values >0.8 will report matches with any polygonal pattern. In conclusion, the methods reported here are suited to detect and analyze spatial, geometric dynamics in optical imaging data.

A hough transform technique for subgraph isomorphism

The Generalized Hough Transform is an established technique for geometric shape matching. An analogous technique is presented here for approximate solution of subgraph isomorphism problems. Its chief advantages are that it can also be used to find partial isomorphisms and that it can be readily implemented in parallel on a network of simple processors.