A Mathematical Overview Of Machine Vision

The work is intended to introduce Machine Vision and Image Processing from a mathematical standpoint. Machine visions origins lie within image capturing, digital image processing and machine learning, however its now becoming geared into a much more powerful tool. This work will give description to mathematical methods used in the current algorithms in machine vision and image processing techniques such as digital watermarking, image compression, noise reduction, etc. In this research, we will explore how machine vision is dependent on image processing algorithms in order to get important information from an image, as well as describe some of the most reliable image processing methods such as Singular Value Decomposition (SVD). Alongside SVD, mathematical models of neural networks and how they are used in the field of machine learning will be discussed. Furthermore, we will discuss some of the applications and limitations of machine vision.