The Internet is a continuously expanding source of multimedia content and information. There are many products in development to search, retrieve, and understand multimedia content. But most of the current image search/retrieval engines,
rely on a image database manually pre-indexed with keywords.
Computers are still powerless to understand the semantic meaning of still or animated image content. Piria (Program for the
Indexing and Research of Images by Affinity), the search engine we have developed brings this possibility closer to reality.
Piria is a novel search engine that uses the query by example method. A user query is submitted to the system, which then
returns a list of images ranked by similarity, obtained by a metric distance that operates on every indexed image signature.
These indexed images are compared according to several different classifiers, not only Keywords, but also Form, Color and Texture,
taking into account geometric transformations and variance like rotation, symmetry, mirroring, etc.
Form - Edges extracted by an efficient segmentation algorithm.
Color - Histogram, semantic color segmentation and spatial color relationship.
Texture - Texture wavelets and local edge patterns.
If required, Piria is also able to fuse results from multiple classifiers with a new classification of index categories:
Single Indexer Single Call (SISC), Single Indexer Multiple Call (SIMC), Multiple Indexers Single Call (MISC)
or Multiple Indexers Multiple Call (MIMC).
Commercial and industrial applications will be explored and discussed as well as current and future development.