Image Classification Using Bag of Visual Words (BoVW)

Authors

  • Abdul Amir Abdullah Karim Department of Computers, University of Technology, Baghdad-Iraq.
  • Rafal Ali Sameer Department of Computers, Collage of Science, University of Baghdad, Baghdad-Iraq

Keywords:

SIFT, Euclidean distance, classification, k-nearest neighbor, Bag of Visual Words

Abstract

In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

Published

2018-12-02

Issue

Section

Articles

How to Cite

[1]
“Image Classification Using Bag of Visual Words (BoVW)”, ANJS, vol. 21, no. 4, pp. 76–82, Dec. 2018, Accessed: Mar. 29, 2024. [Online]. Available: https://anjs.edu.iq/index.php/anjs/article/view/1993