A simple biometrics image descriptor
Khalid Saeed · 2017
There exist many methods for image digital description of objects as one of the important steps before image classification for object recognition. Examples of such methods are momentum expressions based, Fourier descriptors (DFT), geometric features, structural approaches, statistical approaches ? PCA, SVD and LDA, MPEG-7 for shape description, ... and many other known methods based on neural networks, genetic algorithms, hidden Markov chains and so on. These descriptors represent the image code by introducing the image characteristics through what is called the feature vector. Biometrics images are examples of rather specific objects, the human biometric features, and require special care in selecting their descriptor. In the talk the speaker will consider some easy to compute feature vectors based on the modified Circulant Toeplitz matrix minimal eigenvalues. Theory and practice will be considered with biometrics images as examples.