Shape description by image moments is a popular topic in image processing. Standard geometric moments are based on a non-orthogonal basis, which has introduced some problems for image reconstruction. Orthogonal moments such as Zernike and Legendre Moments which use orthogonal polynomials have been introduced to overcome this problem. These however are based on continuous polynomials, and are not really suited to digital images processing which is inherently rooted in a discrete domain. Hence, a new type of discrete orthogonal moments, based on Tchebichef polynomials has emerged.

Sobel edge detection is a popular technique as it can deliver good results, without excessive computational requirements. The technique utilises the theory of optimal smoothing (Gaussian), and optimal differencing.

The Hough Transform (HT) is an image processing operation which enables the extraction of shapes, essentially lines from images. The principle is that there are an infinite number of line that pass though any point, each at a different orientation. The HT aims to determine which of those theoretical lines pass though most features in an image.