Iris Recognition Using Semantic Indexing - Al-Ani, Laith; Altaei, Mohammed; Alwan, Ansam (Iraqi Journal of Science, 2024)
The iris of human eye is one of the most useful traits for biometric recognition.This paper presents an iris recognition system based on semantic indexing. Theproposed system uses the concepts of latent semantic indexing (LSI) for irisrecognition. One technique of LSI is the singular value decomposition (SVD). TheSVD is an information retrieval uses numerical decomposition methods to computeone characteristic value (i.e. SVD) for each iris image to be used as a recognitionfeature. The proposed system consists of two phases: the training and recognition.The training phase is responsible on storing the iris models in the database, while thetask of recognition phase is to compute the similarity measure between the SVD ofthe query iris image and SVDs of the iris images found in the database. Therecognition decision is made according to the normalized similarities and appearedas a text message tells what the identity it is. The successful recognition rate wasabout 96%, which ensure the successful of the employed method and correct path ofcomputations