Feature points’ matching is a popular method in dealing with object recognition and image matching problems. However, variations of images, such as shift, rotation, and scaling, influence the matching correctness. Therefore, a feature point matching system with a distinctive and invariant feature point detector as well as robust description mechanism becomes the main challenge of this issue. We...

Achieving semantic interoperability is a difficult problem with a lot of challenges yet to address. Some of them include matching large-scale data sets, tackling the problem of missing background knowledge, evaluating large scale results, tuning the matching process and doing all of the above in a realistic setting with resource and time constraints. In this paper we report the results of a lar...

Large Scale Graph Matching (LSGM) is one of the fundamental problems in Graph theory and it has applications in many areas such as Computer Vision, Machine Learning, Pattern Recognition and Big Data Analytics (Data Science). Matching belongs to the combinatorial class of problems which refers to finding correspondence between the nodes of a graph or among set of graphs (subgraphs) either precis...

In this paper we present a novel approach to match two images in presenting large scale and rotation changes. The proposed approach is based on scale invariant region description. Scale invariant region is detected by a two-step process and represented by a new descriptor. The descriptor is a two-dimensional gray-level histogram. Different descriptors can be directly compared. In addition, our ...

The purely manual specification of semantic correspondences between schemas is almost infeasible for very large schemas or when many different schemas have to be matched. Hence, solving such large-scale match tasks asks for automatic or semi-automatic schema matching approaches. Large-scale matching needs especially be supported for XML schemas and different kinds of ontologies due to their inc...

The retrieval of images from a large database of images is an important and emerging area of research. Here, a technique to retrieve images based on appearance that works eeectively across large changes of scale is proposed. The database is initially ltered with derivatives of a Gaussian at several scales. A user deened template is then created from an image of an object similar to those being ...