OFFLINE HAND WRITTEN DIGITS RECOGNITION USING SUPPORT VECTOR MACHINE

OFFLINE HAND WRITTEN DIGITS RECOGNITION USING SUPPORT VECTOR MACHINE

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OFFLINE HAND WRITTEN DIGITS RECOGNITION USING SUPPORT VECTOR MACHINE - CodeMint Mint for Sale
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This proposed work seeks to determine how a system for recognition of handwritten digits would be implemented on a modern system. We will focus on the single symbol off-line case of handwriting i.e. the input is a static image containing one symbol. This research will discuss the different stages of a complete recognition system to give an overview of the challenges faced. The limitation is stated below: 
  •  Only one symbol will be recognized at a time.
  • The classifier will only handle binary data and suppose the images have been pre-processed.
  •  Handwriting is subject to high conflict in writing style between different authors. Factors contain size, rotation, lengthening and tilt or the equivalence of dissimilar fonts.
The aim of this project is to develop a system that recognizes offline handwritten digits using Support Vector Machines (SVMs). The objectives are stated below:
  1. To acquire handwritten digits image for all the digits from different people.
  2. To pre-process the entire images for image standardization.
  3. To extract features from the entire images.
  4. To develop a Network for digit recognition using SVMs with the extracted features.

The software used for the implementation of this research is MATLAB.  MATLAB is used to implement the SURF algorithm and the Image and Classification toolboxes are used for reading the images and training the system respectively; it’s also used to design the interface and used to code other part of the program.





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