We represent face images by a set of triangular labeled graphs, each containing information on the appearance and geometry of a 3-tuple of face feature points. Our method automatically learns a model set and builds a ...
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One of the primary aims in human-computer interaction research is to develop an ability to recognize affective state of the user. Such ability is indispensable to have a more human-like nature in human-computer intera...
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ISBN:
(纸本)9783540755548
One of the primary aims in human-computer interaction research is to develop an ability to recognize affective state of the user. Such ability is indispensable to have a more human-like nature in human-computer interaction. However, the researches in this direction are not mature and intensive efforts have only been witnessed recently. This work envisages the possibility of enhancing feature selection phase of emotion detection task to obtain robust parameters which will be determined from verbal information to achieve an improved affective human-computer interaction. As highly informative feature selection is believed to be a more critical factor than classifier itself, recent studies have increasingly focussed on determining features that contribute more to the classification problem. Two new frameworks for multi-class emotion detection problem are proposed in this paper, so as to boost the feature selection algorithms in a way that the selected features will be more informative in terms of class-separability. Evaluation of the selected final features is accomplished by multi-class classifiers. Results show that the proposed frameworks are successful in terms of attaining lower average cross-validation error.
This paper presents the design of a machine vision based system for real time detection of the counterfeit Bangladeshi bank notes. The proposed system works with the denominations of five hundred and one hundred taka....
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ISBN:
(纸本)9781424415502
This paper presents the design of a machine vision based system for real time detection of the counterfeit Bangladeshi bank notes. The proposed system works with the denominations of five hundred and one hundred taka. This system relies on a specific feature of the both five hundred and one hundred taka. The relied feature is not possible to replicate for the counterfeit makers or producers. And there is no foreseeable likelihood that they would be capable to imitate this feature even within a pretty long time. The relied feature is the repeatedly printed "BANGLADESHBANK" on some portions of the notes using microprint technique. The proposed stand alone system captures the portions of the notes with a proprietary scanner called the Grid Scanner [1]. The captured image is then processed by a microcontroller PIC-16F648A or ATMega88 (AVR). The microcontroller then determines the validity of the note based on an OCR technique by looking for the characters 'B', 'A' and 'N' in the scanned image. The success-rate of the counterfeit detection with properly captured image is 100% and the average processing time is 250 milliseconds with above mentioned microcontroller.
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