Sum of Squared Differences

The Sum of Squared Differences (SSD) is a way of determining the correlation between two image regions. It is usually involved when motion compensation needs to be done. SSD is defined as followed: There are some variations of SSD. Like the Zero-mean Sum of Squared Differences (ZSSD): See also: http://siddhantahuja.wordpress.com/2010/04/11/correlation-based-similarity-measures-summary

Shi-Thomasi Corners

Shi-Thomasi is a corner detection algorithm improved from Harris' corner detector. The improvement is the way how a certain region within the image is scored (and thus treated as corner or not). Where the Harris-corner detector determines the score with the eigenvalues and of two regions (the second region is a shifted version of the […]