Feature-driven analysis forms the basis of many shape processing tasks, where detected feature points are characterized by local shape descriptors. Such descriptors have so far been defined to capture regions of interest centered at individual points. Using such regions to compare feature points can be problematic when performing partial shape matching, since the region of interest is typically...

Texture description contributes as one of the most important low-level features in content-based image retrieval. In MPEG-7, homogeneous texture descriptor (HTD), texture browsing descriptor (TBD), and edge histogram descriptor (EHD) have been proposed as texture descriptors. However, no comprehensive evaluation and comparison of these three descriptors have been made. In this paper, we propose...

In this paper we consider models for noncausal processes consisting of discrete-time descriptor dynamics and boundary conditions on the values of the process at the two ends of the interval on which the process is defined. We discuss the general solution and well-posedness of systems of this type and then apply the method of complementary processes to obtain a specification of the optimal smoot...

Pattern clustering is an important data analysis process useful in a wide spectrum of computer vision applications. In addition to choosing the appropriate clustering methods, particular attention should be paid to the choice of the features describing patterns in order to improve the clustering performance. This paper presents a novel feature descriptor, referred as Histogram of Structure Tens...

Development of various image descriptors has greatly contributed to the advancement in image retrieval. Image descriptors can be made invariant to various image changes. In this paper, a new image descriptor is described and its application in image retrieval is evaluated. The descriptor uses the autoencoder concept to reduce the dimension of the feature vector measuing various properties of a ...