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Tomislav Fotak

Bio: Tomislav Fotak is an academic researcher from University of Zagreb. The author has contributed to research in topics: Hand geometry & Biometrics. The author has an hindex of 3, co-authored 5 publications receiving 55 citations.

Papers
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Journal Article
TL;DR: Previous work in the field of signature and writer identification is presented to show the historical development of the idea and a new promising approach in handwritten signature identification based on some basic concepts of graph theory is defined.
Abstract: Handwritten signature is being used in various applications on daily basis. The problem arises when someone decides to imitate our signature and steal our identity. Therefore, there is a need for adequate protection of signatures and a need for systems that can, with a great degree of certainty, identify who is the signatory. This paper presents previous work in the field of signature and writer identification to show the historical development of the idea and defines a new promising approach in handwritten signature identification based on some basic concepts of graph theory. This principle can be implemented on both on-line handwritten signature recognition systems and off-line handwritten signature recognition systems. Using graph norm for fast classification (filtration of potential users), followed by comparison of each signature graph concepts value against values stored in database, the system reports 94.25% identification accuracy.

33 citations

Book ChapterDOI
28 Nov 2012
TL;DR: Mentioned features make hand geometry an ideal candidate for research and development of new acquisition, preprocessing and verification techniques, i.e. personal authentication.
Abstract: Hand geometry is based on the palm and fingers structure, including width of the fin‐ gers in different places, length of the fingers, thickness of the palm area, etc. Although these measurements are not very distinctive among people, hand geometry can be very useful for identity verification, i.e. personal authentication. Special task is to combine some non-descriptive characteristics in order to achieve better identification results. This techni‐ que is widely accepted and the verification includes simple data processing. Mentioned features make hand geometry an ideal candidate for research and development of new acquisition, preprocessing and verification techniques.

14 citations

27 Jun 2012
TL;DR: Researchers in the field of biometrics found that human hand contains some characteristics that can be used for personal identification, including hand geometry and hand shape, which makes them suitable for development of various acquisition and authentication methods.
Abstract: Researchers in the field of biometrics found that human hand contains some characteristics that can be used for personal identification. Some of these are hand geometry and hand shape. These biometric characteristics are more than 30 years old and are very popular and widely accepted among people. That makes them suitable for development of various acquisition and authentication methods. So far, many contact-based and contact-less systems have been developed in the academy and commercial sector. Contact-less biometrics is becoming more important in this field, thus making the researchers to concentrate their efforts in this direction.

7 citations

06 Aug 2011
TL;DR: Basic differences between authentication and identification methods are presented, followed by previous work in the field of handwritten signature identification and main directions in developing an on-line personal identification system based on handwritten signature are presented.
Abstract: Handwritten signature is widely accepted and collectable biometric characteristic. Great entropy makes this characteristic suitable for research and development of new methods for personal authentication and identification. While development of authentication methods based on this biometric characteristic is common thing in academic and research community, there are only few attempts of developing personal identification system based on handwritten signature. This paper presents basic differences between authentication and identification methods, followed by previous work in the field of handwritten signature identification and main directions in developing an on-line personal identification system based on handwritten signature. This work can be considered as the theoretic base for the further development of an on-line handwritten signature identification system.

3 citations

Proceedings Article
16 Jan 2012
TL;DR: The analysis and comparison of communication of Slovenian and Croatian political parties over the Internet is analyzed, with special attention to communication using social networks, such as Facebook or Twitter.
Abstract: In the past decades, information and communication technologies affect all aspects of our lives, including politics. Political parties use the Internet to communicate with their potential voters. This paper will give a short introduction to communication over the Internet in general, description of political parties in question, and the main part of the paper is the analysis and comparison of communication of Slovenian and Croatian political parties over the Internet. Special attention will be payed to communication using social networks, such as Facebook or Twitter.

2 citations


Cited by
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Journal ArticleDOI
TL;DR: A multimodal biometric system for personal identity verification is proposed using hand shape and hand geometry in this paper and outperforms other approaches with the best 0.31% of EER.
Abstract: Shape and geometry features are encoded from contour of the hand only.Robust preprocessing is introduced to cope with the noise and disjoint fingers.Hand orientation and finger registration is applied to provide more flexibility.Two level score fusion is adopted to enhance the verification performance.Promising results are obtained over contact and contactless (IITD) datasets. A multimodal biometric system for personal identity verification is proposed using hand shape and hand geometry in this paper. Shape and geometry features are derived with the help of only contour of the hand image for which only one image acquisition device is sufficient. All the processing is done with respect to a stable reference point at wrist line which is more stable as compared to the centroid against the finger rotation and peaks and valleys determination. Two shape based features are extracted by using the distance and orientation of each point of hand contour with respect to the reference point followed by wavelet decomposition to reduce the dimension. Seven distances are used to encode the geometrical information of the hand. Shape and geometry based features are fused at score levels and their performances are evaluated using standard ROC curves between false acceptance rate, true acceptance rate, equal error rate and decidability index. Different similarity measures are used to examine the accuracy of the introduced method. Performance of system is analyzed for shape based (distance and orientation) and geometrical features individually as well as for all possible combinations of feature and score level fusion. The proposed features and fusion methods are studied over two hand image datasets, (1) JUET contact database of 50 subjects having 10 templates each and (2) IITD contactless dataset of 240 subjects with 5 templates each. The proposed method outperforms other approaches with the best 0.31% of EER.

61 citations

Journal ArticleDOI
TL;DR: The approaches taken from other researches on preprocessing, feature extraction and classification stage specifically for recognizing individual identity for biometrics trait using finger-vein are discussed.
Abstract: Biometrics trait using finger-vein has attracted numerous attention from researchers all over the world since the last decade. Various approaches have been proposed in regard to improving the accuracy of identification result. This paper discusses on the approaches taken from other researches on preprocessing, feature extraction and classification stage specifically for recognizing individual identity. The strengths and weaknesses of these approaches are critically reviewed. The classification approach using machine learning method is highlighted to determine the future direction and to fill the research gap in this field.

53 citations

Journal ArticleDOI
TL;DR: A novel hand biometric authentication method based on measurements of the user’s stationary hand gesture of hand sign language is proposed, which shows up to 93.75% recognition accuracy.
Abstract: A novel hand biometric authentication method based on measurements of the user’s stationary hand gesture of hand sign language is proposed. The measurement of hand gestures could be sequentially acquired by a low-cost video camera. There could possibly be another level of contextual information, associated with these hand signs to be used in biometric authentication. As an analogue, instead of typing a password ‘iloveu’ in text which is relatively vulnerable over a communication network, a signer can encode a biometric password using a sequence of hand signs, ‘i’ , ‘l’ , ‘o’ , ‘v’ , ‘e’ , and ‘u’. Subsequently the features from the hand gesture images are extracted which are integrally fuzzy in nature, to be recognized by a classification model for telling if this signer is who he claimed himself to be, by examining over his hand shape and the postures in doing those signs. It is believed that everybody has certain slight but unique behavioral characteristics in sign language, so are the different hand shape compositions. Simple and efficient image processing algorithms are used in hand sign recognition, including intensity profiling, color histogram and dimensionality analysis, coupled with several popular machine learning algorithms. Computer simulation is conducted for investigating the efficacy of this novel biometric authentication model which shows up to 93.75% recognition accuracy.

46 citations

Book ChapterDOI
02 Aug 2015
TL;DR: This study demonstrates that the Leap Motion can indeed by used successfully to both authenticate users at login as well as while performing continuous activities.
Abstract: The Leap Motion controller is a consumer gesture sensor aimed to augment a user's interactive experience with their computer Using infrared sensors, it is able to collect data about the position and motions of a user's hands This data allows the Leap to be used as an authentication device This study explores the possibility of performing both login as well as continuous authentication using the Leap Motion device The work includes classification of static data gathered by the Leap Motion using trained classifiers, with over 99i?ź% accuracy In addition, data was recorded from the users while utilizing the Leap Motion to read and navigate through Wikipedia pages A template was created using the user attributes that were found to have the highest merit The algorithm found when matching the template to the users newly collected data, the authentication provided an accuracy of over 98i?ź%, and an equal error rate of 08i?ź% even for a small number of attributes This study demonstrates that the Leap Motion can indeed by used successfully to both authenticate users at login as well as while performing continuous activities As the Leap Motion is an inexpensive device, this raises the potential of using its data in the future for authentication instead of traditional keyboard passwords

36 citations

Patent
19 May 2008
TL;DR: An object of the present invention, but relates to personal identification in environments where non-contact is required, use of which is not clear position shift finger vein pattern image, to realize personal identification with high accuracy.
Abstract: An object of the present invention, but relates to personal identification in environments where non-contact is required, use of which is not clear position shift finger vein pattern image, to realize personal identification with high accuracy. In order to achieve the above object, and as a method of extracting a vein pattern contained in the means for acquiring a finger vein pattern image by a non-contact, and the obtained image using the outline of the finger based on the hand and means for performing a rotation correction, and statistically this means for obtaining the whole vein pattern with the strong characteristic in the blood vessel pattern shown by repeating the means for normalizing the location of the finger image, a visit to any position arbitrary dark by the luminance point length portion in the image and matching means for comparing only the parts, dividing the image into small regions and in each small region by performing the matched independently, and a means for evaluating positional deviations where matching is recognized. Finger vein pattern input interface, a light source, an optical filter, CCD camera, image capture board, the finger insertion opening, identification claimant, automatic doors, the password input keys, a fingerprint input interface, and an iris image pick-

36 citations