Quick invariant signature extraction from binary images

It is shown how basic geometric notions can be used to extract an image signature independently of position, orientation and size. Simple primitives as lengths and slopes remain invariant by affine 2D similarity transformations. They can easily be used to define the invariant signature of an image. Contrary to the previous work in this area, images can be directly analyzed. This means that the extraction of interest points of the image is avoided. The method remains formal and no estimation or compression is needed. It is formally demonstrated that 100% of transformations are taken into consideration and that the signature of the image is totally invariant. The Quick Invariant Signature (QIS) extraction is a formal and fast method. It can be used either, only for signature extraction, or be integrated into a neural architecture for both extraction and classification. Unusual invariances such as cylindrical translation or toric translation are also defined by QIS.