We propose a training-free texture classification scheme, outperforming methods that use training. This we demonstrate not only for traditional texture benchmarks, but also for the identification of materials and writers of musical scores. State-of-the-art methods operate using local descriptors, their intermediate representation over trained dictionaries, and classifiers. For the first two ste...

Dynamic texture (DT) is an extension of texture to the temporal domain. How to segment DTs is a challenging problem. In this paper, we address the problem of segmenting DT into disjoint volumes in an unsupervised way. DTs might be different from their spatial mode (i.e., appearance) and/or temporal mode (i.e., motion field). To this end, we develop a framework based on the appearance and motion...

Automated data analysis and pattern recognition techniques are the requirements of biological and proteomicsresearch studies. The analysis of proteins consists of some stages among which the analysis of two dimensionalelectrophoresis (2-DE) images is crucial. The aim of image capturing is to generate a Photostat that can be used infuture works such as image comparison. The researchers introduce...

A new texture descriptor, called CSG vector, is proposed for image retrieval and image segmentation in this paper. The descriptor can be generated by composing the gradient vectors obtained from the sub-images through a wavelet decomposition of a texture image. By exercising a database containing 2400 images which were cropped from a set of 150 types of textures selected from the Brodatz Album,...

Now a days, applications in the field of surveillance, banking and multimedia equipment are becoming more important, but since each application related to face analysis demands different requirements on the analysis process, almost all algorithms and approaches for face analysis are application dependent and a standardization or generalization is quite difficult. For that reason and since many ...

We propose a compact descriptor for the purpose of dense image matching and object recognition. The descriptor is calculated based on local gradients about each point in an image. It contains the averages of gradients at four different windows surrounding a center point. The descriptor is calculated much faster than histogram of oriented gradients (HOG). Additionally, it will be shown that it i...

Most existing feature-point matching algorithms rely on photometric region descriptors to distinct and match feature points in two images. In this paper, we propose an efficient feature-point matching algorithm for finding point correspondences between two uncalibrated images separated by small or mid camera baselines. The proposed algorithm does not rely on photometric descriptors for matching...