Improvement of the Recognition Rate by Random Forest

Abstract

In this paper; we introduce a system of automatic recognition of characters based on the Random Forest Method in non-constrictive pictures that are stemmed from the terminals Mobile phone. After doing some pretreatments on the picture, the text is segmented into lines and then into characters. In the stage of characteristics extraction, we are representing the input data into the vector of primitives of the zoning types, of diagonal, horizontal and of the Zernike moment. These characteristics are linked to pixels’ densities and they are extracted on binary pictures. In the classification stage, we examine four classification methods with two different classifiers types namely the multi-layer perceptron (MLP) and the Random Forest method. After some checking tests, the system of learning and recognition which is based on the Random Forest has shown a good performance on a basis of 100 models of pictures.

Authors and Affiliations

Youssef Rachidi, Zouhir Mahani

Keywords

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  • EP ID EP390188
  • DOI 10.9790/9622- 0702043743.
  • Views 142
  • Downloads 0

How To Cite

Youssef Rachidi, Zouhir Mahani (2017). Improvement of the Recognition Rate by Random Forest. International Journal of engineering Research and Applications, 7(2), 37-43. https://europub.co.uk/articles/-A-390188