Feature extraction code in matlab

1. How do I extract a feature in Matlab?
2. What is feature extraction with example?
3. How to do feature extraction?
4. How to extract Gabor features in Matlab?

How do I extract a feature in Matlab?

The simplest way to generate code for automatic feature extraction is to use the Export button in the Feature Designer tab and select Generate Function for Features. Your selection opens a set of options that allow you to specify the features to include from the feature table that you select.

What is feature extraction with example?

Feature Extraction uses an object-based approach to classify imagery, where an object (also called segment) is a group of pixels with similar spectral, spatial, and/or texture attributes. Traditional classification methods are pixel-based, meaning that spectral information in each pixel is used to classify imagery.

How to do feature extraction?

Feature Extraction aims to reduce the number of features in a dataset by creating new features from the existing ones (and then discarding the original features). These new reduced set of features should then be able to summarize most of the information contained in the original set of features.

How to extract Gabor features in Matlab?

The second function named "gaborFeatures. m" extracts the Gabor features of an input image. It creates a column vector, consisting of the Gabor features of the input image. The feature vectors are normalized to zero mean and unit variance.