Main Article Content
Most of the industries and business organizations use various kinds of biometric patterns such as face, finger, palm, vein, skin surface, footprint and some structural parts of the human body and also to consider some video patterns of the stakeholder/customeras secure data for the customers /stakeholders in terms of authentication / verification / authorization/ recognition of traits and also use secure agents for the personal data as well as social/ business/ web/ banking transactions. Also, the government sector use the biometric patterns of stakeholders to claim the government policies, facilities and issue the authorized cards like aadhaar, driving license, passport, pancard etc.., for their needs. The stake holders would provide different patterns of his/ her poster as face, fingerprint, palm, vein, footprint, and/ or other structural patterns of the human body in terms of 2D and 3D patterns. In order to compute such patterns the extraction of features/ recognition of patterns is complex and NP-hard due to the representation of captured patterns with noise or acquisition of sensed data or noisy of sensing devices. To overcome such complexities the vector logic (cognitive logic) models for minimizing the noise and computations of best features for recognition of such patterns.
How to Cite
, D. R. U. R. (2018). Feature Evolution using Factorization Methods in Multimodal Authentication � Smart Security Devices. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 4(1), 200–202. Retrieved from https://ijfrcsce.org/index.php/ijfrcsce/article/view/990