METHOD AND DEVICE FOR AUTOMATIC PATTERN RECOGNITION

• US 20100217572A1
• Filed: 07/31/2008
• Published: 08/26/2010
• Est. Priority Date: 07/31/2007
• Status: Abandoned Application

• Current Assignee: Technische Universitã¤T Berlin (Tu)
• Original Assignee: Technische Universitã¤T Berlin (Tu)
• Inventors: Kuhn, Steffen, Guhmann, Clemens
• Application Number:
  US12/671,248
• Publication Number:
  US 20100217572A1
• Time in Patent Office: Days
• US Class Current: 703/2
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06F 18/2321 using statistics or function optimisation, e.g. modelling of probability density functions
• CPC Class Codes: G06F 18/295 Markov models or related models, e.g. semi-Markov models; Markov random fields; Networks embedding Markov models
• CPC Class Codes: G06V 10/761 Proximity, similarity or dissimilarity measures
• CPC Class Codes: G06V 10/763 Non-hierarchical techniques, e.g. based on statistics of modelling distributions

Abstract

The invention relates to a method for the automatic pattern recognition in a sequence of electronic data by means of a electronic data processing in a data processing system, during which the sequence of electronic data is compared with parameterised model data representing at least one sample sequence, in an analysis and where at least one sample sequence is recognised if training data is processed to a set of characteristic vectors of the same length and with the same information content, from which the parameterised model data is derived, by means of a dynamic time warping method during the formation of the parameterised model data, if it has been established during the analysis that the model data enclosed by the parameterised model data, which are allocated to at least one sample sequence, occurs with a level of similarity exceeding the similarity threshold. In addition, the invention relates to a device for automatic pattern recognition in a sequence of electronic data by means of electronic data processing with a data processing system.

Claims

1. A method for automatic pattern recognition in a sequence of electronic data by means of electronic data processing in a data processing system, where the sequence of electronic data is compared in an analysis with parameterized model data representing at least one pattern sequence in an analysis and where at least one pattern sequence will have been recognised, where the training data is processed to a set of feature vectors of equal length and the same content as the training data, from which the parameterised model data has been derived, by means of a dynamic time warping method, during the formation of the parameterized model data, if it has been established during the analysis that the model data enclosed by the parameterised model data allocated to at least one pattern sequence occurs with a level of similarity exceeding the similarity threshold.

2. The method in accordance with claim 1, characterised in that the parameterised model data are derived from the set of feature vectors, by parameterizing a feature vector classifier.

3. The method in accordance with claim 2, characterised in that a Bayes classifier with Parzen window density estimation is used.

4. The method in accordance with claim 1, characterised in that the level of similarity L(N,j) for a point in time j of the analysis, for the partial sequence of electronic data from the sequence of electronic data, is established as follows:

$L<br><br>\left(i,j\right);<br><br>=\underset{\mathrm{\alpha <br><br>}=0,{\mathrm{\dots <br><br>\alpha <br><br>}}_m-1}{\max }<br><br>\left\{L<br><br>\left(i-1,j-\mathrm{\alpha <br><br>}\right)+\log <br><br>\left(p_{t,i}<br><br>\left(\mathrm{\alpha <br><br>}\right)\right)\right\}+c<br><br><br><br>\log <br><br>\left(p_{e,i}<br><br>\left(x_j\right)\right)$

where x_j, p_t,i(·

) and p_e,i(·

), the elements of the sequence of electronic data, the i elements of al N elements of parameterised model data and c and a_m, are constants to be selected empirically.

5. A device for automatic pattern recognition in a sequence of electronic data by means of electronic data processing, by a data processing system having the following characteristics:

pattern recognition means that is configured to compare the sequence of electronic data with parameterised data in an analysis and to recognise at least one pattern sequence, if it has been established during the analysis that the model data enclosed by the parameterised model data allocated to at least one pattern sequence occurs with a level of similarity exceeding the similarity threshold and

model data creation means configure to create the parameterised model data using training data and to process the training data to a set of feature vectors of the same length and with the same information content as the training data from which the parameterised model data has been derived by means of a dynamic time warping method and

provision means configured to provide electronically assessable identification information by recognising at least one pattern sequence for an output.