G. S. Badrinath

Learn More
This paper presents a novel combination of local-local information for an efficient finger-knuckle-print (FKP) based recognition system which is robust to scale and rotation. The non-uniform brightness of the FKP due to relatively curvature surface is corrected and texture is enhanced. The local features of the enhanced FKP are extracted using the scale(More)
The key concern of indexing is to retrieve small portion of database for searching the query. In the proposed paper iris database is indexed using energy histogram. The normalised iris image is divided into subbands using multiresolution DCT transformation. Energy based histogram is formed for each subband using all the images in the database. Each(More)
This paper presents a robust iris recognition system using local feature descriptor. The proposed biometric system accounts for two crucial issues. Firstly, iris texture is usually occluded by upper and lower eyelids. To handle this problem, a novel sector based normalisation is proposed. In this approach only non-occluded region is extracted by forming(More)
This paper describes the design and development of a prototype of robust biometric system for personnel verification. The system uses features extracted using scale invariant feature transform (SIFT) operator of human hand. The hand image for features is acquired using a low cost scanner. The palmprint region extracted is robust to hand translation and(More)