Beginner Question Extracting Features for Image Classification

1. What is feature extraction in image classification?
2. How features are extracted from an image?
3. Why feature extraction is important in image processing?

What is feature extraction in image classification?

Feature extraction refers to the process of transforming raw data into numerical features that can be processed while preserving the information in the original data set. It yields better results than applying machine learning directly to the raw data.

How features are extracted from an image?

Feature extraction is a part of the dimensionality reduction process, in which, an initial set of the raw data is divided and reduced to more manageable groups. So when you want to process it will be easier. The most important characteristic of these large data sets is that they have a large number of variables.

Why feature extraction is important in image processing?

Feature extraction increases the accuracy of learned models by extracting features from the input data. This phase of the general framework reduces the dimensionality of data by removing the redundant data. Of course, it increases training and inference speed.