Biomimetics
Saeed Rashidi; Seyed Mohammad Reza Hashemi Golpayegani; Ali Fallah; Farzad Towhidkhah
Volume 4, Issue 1 , June 2010, , Pages 33-44
Abstract
In drawing movements, the constraints imposed on the trajectory geometry properties and kinematics are known with two laws: 2/3 power law and isochrony phenomenon. In this paper experiments have been designed to study the relation between two empirical laws in straight and curved patterns of drawing ...
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In drawing movements, the constraints imposed on the trajectory geometry properties and kinematics are known with two laws: 2/3 power law and isochrony phenomenon. In this paper experiments have been designed to study the relation between two empirical laws in straight and curved patterns of drawing movements in 16-18 years old subjects. Providing two models of power is indicated that in drawing movements, invariant features can be defining. These features are independent of subject, direction and size of trajectory and together they can simplify the role of the upper motor control system and decrease the degrees of freedom and the computational complexity.
Saeed Rashidi; Ali Fallah; Farzad Towhidkhah
Volume 4, Issue 2 , June 2010, , Pages 135-148
Abstract
Many methods are introduced for estimating the similarities or differences of time signals. One of theses methods, DTW algorithm, is also a utility for other domains including classification, data mining and matching regions between two time signals. DTW algorithm minimizes points distance between two ...
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Many methods are introduced for estimating the similarities or differences of time signals. One of theses methods, DTW algorithm, is also a utility for other domains including classification, data mining and matching regions between two time signals. DTW algorithm minimizes points distance between two signals by contracting or expanding the time axes to find the corresponding points. In this paper, with modification of the local constraints in DTW, a powerful method is proposed for measuring the global or local similarities between two signals. In addition to increasing the accuracy of signals distance measurements and decreasing the classification error, proposed algorithm is more stable than classic DTW against variations of structure and time signal source. The proposed method for dynamic signature verification was applied to a dataset of signatures from Turkish, Chinese and English people. The results of the experiments based on Fisher, Parzen Window and Support Vectors Machine classifications, showed that equal error rate (EER) is 1.46% and 3.51% with universal threshold for random and skilled forgeries, respectively.
Saeed Rashidi; Ali Fallah; Farzad Towhidkhah
Volume 4, Issue 3 , June 2010, , Pages 219-230
Abstract
Nowadays, fast and accurate algorithms for signature verification are very attractive. In the area of dynamic signature verification, the features are classified into two groups: parametric and functional features. In parametric algorithms, although the speed of features extraction and classification ...
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Nowadays, fast and accurate algorithms for signature verification are very attractive. In the area of dynamic signature verification, the features are classified into two groups: parametric and functional features. In parametric algorithms, although the speed of features extraction and classification process is faster than function based approaches but they are less accurate. The goal of this paper is modeling of the velocity signal that its pattern and properties are stable for a person. With using pole-zero models based on discrete cosine transform, a precise method is proposed for modeling and then features are extracted from strokes. These features are the deference of pole angles of strokes. Applying linear, parzen window and support vector machine classifiers, the proposed algorithm was tested on data set from Persian, Chinese, English and Turkish people and with common threshold, resulted equal error rates of 1.25% and 1.78% in the random and skilled forgeries, respectively.
Biomechanical Motor Control / Motor Control of Human Movement
Saeed Rashidi; Ali Fallah; Farzad Towhidkhah
Volume 1, Issue 4 , June 2007, , Pages 269-280
Abstract
Dynamic signature verification based on temporal features are more precise than the static methods because in addition to position information of the drawing pattern, it uses local and global features extracted from velocity, acceleration, pressure and pen angle signals, while static methods only use ...
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Dynamic signature verification based on temporal features are more precise than the static methods because in addition to position information of the drawing pattern, it uses local and global features extracted from velocity, acceleration, pressure and pen angle signals, while static methods only use image information. In this study, we segmented the signature patterns using the basic role of velocity in the control process of skilled movements and then the function features were extracted. In order to signal the matching evaluation, we applied five generalized functions and five weighting strategies for score level fusion. The results showed that the correlation criterion had the minimum error. The experiments on the database, consisting of persons of Persian, Chinese and English, showed that the skilled forgeries obtained an equal error rate (EER) of 0.87% and 1.24% for the user and universal thresholds, respectively.
