fendy07 / sift-mask

This is about my project in Image Classification focus to Pattern Recognition about Cirebon Mask Classification in MATLAB. You can check how to using the model dataset and classification model data with MATLAB.

Scale Invariant Feature Transform for Cirebon Mask Classification

Fendy Hendriyanto

The vast diversity of art in Indonesia generates much interest both domestically and internationally. One of the prominent cultures is the Cirebon Mask. There are five types of Cirebon masks: Panji, Samba, Rumyang, Tumenggung, and Klana. In this research, Cirebon masks are classified using digital image processing techniques using Scale-Invariant Feature Transform, while K-Nearest Neighbour, Support Vector Machines, and Random Forest are the classifiers.

Methodology

• Data Collection
  • The dataset was collected using two different ways: captured the Cirebon mask images using a camera and collected Cirebon mask images using a search engine application.
• Pre-Processing
  • In this step, the background images were removed manually, this made the background black. After removing the background images, each image is resized to 50 x 50 pixel resolution.
• Feature Extraction
  • Scale Invariant Feature Transform (SIFT)
• Classification
  • K-Nearest Neighbor
  • Support Vector Machine
  • Random Forest

For details, you can see my article on Medium.