Paraskevas Diamantatos He holds a B.Sc. in Information and Communication Systems Engineering from the dept. of Information and Communications Systems Engineering of the University of the Aegean (U.o.A). He holds a M.Sc. in Information Management and Web Technologies, which was completed in 2011-2012, and one in Security of Information and Communication Systems, completed in 2012-2013, both from U.o.A. Currently, he is a PhD candidate, specializing in Optical Character Recognition in U.o.A.
Computer Vision, Artificial Intellegence , Robotics, Graphics and Information and Communication Systems Security
Abstract
In this paper, a feature that is based on statistical directional features is presented. Specifically, an improvement of the statistical feature: edge hinge distribution, is attempted. Furthermore, different matching techniques are applied. For the evaluation, the Firemaker DB was used, which consists of samples from 250 writers, including 4 pages per writer. The suggested feature, the skeleton hinge distribution, achieved accuracy of 90.8% using nearest neighbor with Manhattan distance for matching.
Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.
Abstract
The state-of-the-art writer identification systems use a variety of different features and techniques in order to identify the writer of the handwritten text. In this paper several statistical and model based features are presented. Specifically, an improvement of a statistical feature, the edge hinge distribution, is attempted. Furthermore, the combination of this feature with a model-based feature is explored, that is based on a codebook of graphemes. For the evaluation, the Firemaker DB was used, which consists of 250 writers, including 4 pages per writer. The best result for the statistical suggested approach, the skeleton hinge distribution, achieved accuracy of 90,8%, while the combination of this method with the codebook of graphemes reached 96%.
Abstract
This paper presents a novel procedure for localizing text on scene photos. It takes advantage of the fact that text should present some contrast in comparison with the background, in order to be distinguished by the human eye. A procedure of binarization is applied in order to create appropriate images for the text detection. The connected components of the image are extracted and some heuristic rules are applied in order to identify areas containing text. Finally, the overlaps are handled and the false detections are rejected. The method is evaluated using images of natural scene taken from the robust reading competition of ICDAR2011. The results are promising and some useful conclusions are drawn.
Abstract
Blindness is the condition of lacking visual perception due to physiological or neurological factors. Blind people do not have the full perception of the surrounding environment, though navigating, in an unknown environment or/and with obstacles on route, can be a very difficult task. In this paper, an information mobile system is presented, that acts as an electronic travel aid, and can guide a blind person through a route, inform him about imminent obstacles in his path and help him orientate himself. The current prototype consists of a mobile phone, and the developed application.
Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.
Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.
Copyright Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted or mass reproduced without the explicit permission of the copyright holder.