Preprocessing of character images is an important step in recognition. We describe a method of enhancing binary character images to assist the subsequent recognition process in both handwritten and machine-printed documents. The method performs selective and adaptive stroke "filling" with a neighborhood operator which emphasizes stroke connectivity. An improvement of 7% points was realized in r...

Currently there are lots of plagiarism detection approaches. But few of them implemented and adapted for Persian languages. In this paper, our work on designing and implementation of a plagiarism detection system based on preprocessing and NLP technics will be described. And the results of testing on a corpus will be presented. Keywords— External Plagiarism, Plagiarism, Copy detection, natural ...

The skeleton is a continuous planar shape for representation as a kind of primitive of the original. The skeleton efficiently concentrates the topological information of the original shape. It is particularly useful for representing amorphous, irregular shapes that cannot be treated by more conventional geometrical methods. The possible applications include the creation of shape primitives, cur...

This paper presents a scalable solution to the problem of tracking objects across spatially separated, uncalibrated, non-overlapping cameras. Unlike other approaches this technique uses an incremental learning method to create the spatio-temporal links between cameras, and thus model the posterior probability distribution of these links. This can then be used with an appearance model of the obj...

Finding non-Gaussian components of high-dimensional data is an important preprocessing step for efficient information processing. This article proposes a new linear method to identify the “nonGaussian subspace” within a very general semi-parametric framework. Our proposed method, called NGCA (non-Gaussian component analysis), is based on a linear operator which, to any arbitrary nonlinear (smoo...

One of the challenges of Volume Modelling is the definition of theoretical frameworks to support object manipulation and representation. Opposite to what is seen in the field of surface modelling, few satisfactory tools have been presented that ensure topological robustness to volumetric models. In this paper we offer one such mathematical framework for volumetric model definition based on tetr...

Reproducing experiments is an important instrument to validate previous work and build upon existing approaches. It has been tackled numerous times in different areas of science. In this paper, we introduce an empirical replicability study of three well-known algorithms for syntactic centric aspect-based opinion mining. We show that reproducing results continues to be a difficult endeavor, main...

Segmenting documents into discrete, sentence-like units is usually a first step in any natural language processing pipeline. However, current segmentation tools perform poorly on text that contains markup. While stripping markup is a simple solution, we argue for the utility of the extra-linguistic information encoded by markup and present a scheme for normalising markup across disparate format...

Many image processing tasks exist and segmentation is one of them. We are focused on the mean-shift segmentation method. Our goal is to improve its speed and reduce the over-segmentation problem that occurs with small spatial bandwidths. We propose new mean-shift method called Hierarchical Layered Mean Shift. It uses hierarchical preprocessing stage and stacking hierarchical segmentation output...

Social media provide a rich source of author-identified text that can be used for personality profiling. However, differences in length and number of entries, syntax, abbreviations, spelling and grammar errors, and topics can affect type and difficulty of preprocessing to extract appropriate text, accuracy of training, time period sampling for training texts, and rate of degradation of accuracy...