Motion detection can play an important role in many vision tasks. Yet image motion can arise
from" uninteresting" events as well as interesting ones. In this paper, salient motion is …

This paper describes a method for robust offline writer identification. We propose to use
RootSIFT descriptors computed densely at the script contours. GMM supervectors are used …

The text-independent approach to writer identification does not require the writer to write
some predetermined text. Previous research on text-independent writer identification has …

Convolutional neural networks (CNNs) have recently become the state-of-the-art tool for
large-scale image classification. In this work we propose the use of activation features from …

Offline handwriting has become a very important part in the field of behavioral biometrics. In
this paper, we proposed an approach to identify writers from their handwritten documents …

Writer's identification from a handwritten text is one of the most challenging machines
learning problems because of the variable handwritten sources, various languages, the …

Local feature descriptors in combination with bag of (visual) words have recently become
the state of the art in writer identification. In this work we propose the use of Zernike …

Handwriter identification aims to simplify the task of forensic experts by providing them with
semi-automated tools in order to enable them to narrow down the search to determine the …

This paper investigates the problem of writer identification from handwriting samples in
Arabic. The proposed technique relies on extracting small fragments of writing which are …

Understanding handwritten documents is a vital and challenging problem that attracts many
researchers in the fields of forensic and authentication science. This paper presents an …