Data mining is often called 'knowledge discovery in databases', since it is about finding new and useful information in a lot of data. The goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use.
The actual data mining task is the automatic or semi-automatic analysis of large quantities of data to extract previously unknown interesting patterns such as groups of data records (cluster analysis), unusual records (anomaly detection) and dependencies (association rule mining).
Digital image processing deals with manipulation of digital images through a digital computer. It is a sub-field of signals and systems but focus particularly on images. Digital Image Processing focuses on developing a computer system that is able to perform processing on an image. The input of that system is a digital image and the system process that image using efficient algorithms, and gives an image as an output.
Face recognition has its routes in various fields of applied Mathematics, namely image processing and data mining and it became a fast developing field on it's own right. A facial recognition system is a computer application for identifying a person from a digital image. It is typically used in security systems, but it is used also for other purposes, like it was adopted for eliminating duplicate votes in the Mexican presidential elections.
Similar image recognition methods are used for several purposes. Among others it is used for car license plate recognition, for analyzing sport events, in cartography, for automatic navigation, etc.
During my thesis work I designed and also created a face recognition system. The system is based on Convolutional Artificial Neural Network image classifier. GPU is used to enhance ANN training speed, and Keras framework made my progress faster by providing high level API for ANN creation.