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Histogram of Oriented Gradients-Based Digit Classification Using Naive Bayesian Classifier

  • Shashwati Mishra
  • Mrutyunjaya Panda
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 710)

Abstract

Classification helps in grouping the objects according to their characteristics or features, which is essential for predicting the behavior of objects, simplifying the process of searching in a large database, detecting specific objects, etc. Advancement in information technology has increased the need for classification of text documents, image, video, audio dataset for easy and accurate retrieval of required information. Selecting features where the most relevant information lies is one of the important steps before classification. In this paper, gradient information is used for feature extraction with the help of histogram of oriented gradients technique. The simplicity of naive Bayesian classifier makes it suitable for large databases. The accuracy and ROC curve prove the effectiveness of the proposed method.

Keywords

Histogram of oriented gradients Bayes’ theorem Naive Bayesian classifier Supervised learning Digit classification 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer Science and ApplicationsUtkal University, Vani ViharBhubaneswarIndia

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