Main Reference PaperImproving Offline Handwritten Text Recognition with Hybrid HMM/ANN Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, April 2011.
  • Offline handwritten text is recognized using the models namely hybrid Hidden Markov Model (HMM)/Artificial Neural Network (ANN). Preprocessing of the text is done in terms of removal of slope and slant from the text followed by identification of text throughemission probabilities.

+ Description
  • Offline handwritten text is recognized using the models namely hybrid Hidden Markov Model (HMM)/Artificial Neural Network (ANN). Preprocessing of the text is done in terms of removal of slope and slant from the text followed by identification of text throughemission probabilities.

  • To proposes the use of hybrid Hidden Markov Model (HMM)/Artificial Neural Network (ANN) models for recognizing unconstrained offline handwritten texts.

  • To propose a new technique to remove slope and slant from handwritten text and to normalize the size of text images with supervised learning methods.

+ Aim & Objectives
  • To proposes the use of hybrid Hidden Markov Model (HMM)/Artificial Neural Network (ANN) models for recognizing unconstrained offline handwritten texts.

  • To propose a new technique to remove slope and slant from handwritten text and to normalize the size of text images with supervised learning methods.

  • Multiplayer perceptron based preprocessing is contributed in which slope and slant is removed and normalized.

+ Contribution
  • Multiplayer perceptron based preprocessing is contributed in which slope and slant is removed and normalized.

  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1, J2SE

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1, J2SE

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

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