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An Introduction to Image Classification

Description

In this tutorial, two main areas will be covered using Textural Images Dataset:

  1. Textural Features Methods: (Grey Level Co-occurrence Matrix(GLCM), Local Binary Pattern(LBP) and Local Directional Pattern(LDP))

  2. Classification using Support Vector Machine (SVM) and Naive Bayes(NB).

Both Features Extraction and Classification will be implemented using Python.

Texture is a very important factor in computer vision; it represents the first level of spatial properties that can be extracted from digital image. Texture can be defined as relationship between gray level in neighboring pixels.

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