Image Augmentation for Deep Learning using Keras and Histogram Equalization

In order to combat the high expense of collecting thousands of training images, image augmentation has been developed in order to generate training data from an existing dataset. Image Augmentation is the process of taking images that are already in a training dataset and manipulating them to create many altered versions of the same image. This both provides more images to train on, but can also help expose our classifier to a wider variety of lighting and coloring situations so as to make our classifier more robust.

This is the single best post I've seen on the topic of image pre-processing, an increasingly critical skill in a wide range of use cases. The writeup and code for histogram normalization (pictured above) was particularly cool.

Whether of not you work with image data today, this is a must-read.


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