Affine Transformation- Image Processing In TensorFlow- Part 1

Affine Transformation helps to modify the geometric structure of the image, preserving parallelism of lines but not the lengths and angles.

What You Will Learn?

• Introduction to Affine Transformation
• Different Affine Transformations like Rotation, Shear, Scale and Translation
• Math Behind Affine Transformation
• Implementation of Affine Transformation In Tensorflow

Let’s Start…

Introduction to Affine Transformation

Affine Transformation helps to modify the geometric structure of the image, preserving parallelism of lines but not the lengths and angles. It preserves collinearity and ratios of distances. It is one type of method we can use in Machine Learning and Deep Learning for Image Processing and also for Image Augmentation.

This technique is also used to correct Geometric Distortions and Deformations that occur with non-ideal camera angles. Ex: Satellite Imagery.

The Affine Transformation relies on matrices to handle rotation, shear, translation and scaling.

We will be using an image as a reference to understand the things more clearly.