Recognition of Amazigh characters using SURF & GIST descriptors

نویسندگان

  • H. Moudni
  • M. Er-rouidi
  • M. Oujaoura
چکیده

In this article, we describe the recognition system of Amazigh handwritten letters. The SURF descriptor, specifically the SURF-36, and the GIST descriptor are used for extracting feature vectors of each letter from our database which consists of 25740 manuscripts isolated Amazigh characters. All the feature vectors of each letter form a training set which is used to train the neural network so that it can calculate a single output on the information it receives. Finally, we made a comparative study between the SURF-36 descriptor and GIST descriptor. Keywords—SURF; GIST; Principal Component Analysis; Neural Network; Amazigh Characters.

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تاریخ انتشار 2013