Retina Recognition
3 articles · search the full text for this term
-
Retina Recognition System Using Wavelet based Neural Network Algorithm
Abstract: This paper presents an approach of wavelet feature-based retina recognition system using back-propagation learning neural network algorithm. After acquiring the retinal image, at first vessels were segmented from the image. Then the feature extraction was carried out by analyzing the segmented retinal image using multiresolution analysis through the wavelet-based approach. Then extracted features were fed to the back-propagation learning neural network algorithm to create the learned template which was used …
Published in Current Trends in Signal Processing · Vol. 5, Issue 2, 2015 · pp. 35–39 Read article
-
Retina Recognition System using PCA-based Discrete Hidden Markov Model
Abstract: In this paper, a unique approach of retina recognition system has been proposed. Principal component analysis based dimensionality reduction technique has been used here and discrete hidden Markov model (DHMM) has been applied to classify the retinal images. The retinal images are taken from DRIVE retina database. Then some image pre-processing techniques such as image scaling, median filtering-based noise reduction and edge-detection techniques have been used to ready the retinal …
Published in Journal Of Network security · Vol. 3, Issue 1, 2015 · pp. 28–32 Read article
-
Iris and Retina Recognition based Multimodal Person Identification System
Abstract: Nowadays we are living in such an era of science where authentication has become one of the greatest challenges in the thorny issue of security. There are many ways in which authentication can be provided, but among them biometric authentication is indispensable. Among all the biometrics in use today the highest level of uniqueness, performance, universality and circumvention are provided by eye based biometrics (i.e., iris and retina recognition). This …
Published in Current Trends in Information Technology · Vol. 5, Issue 1, 2015 · pp. 22–28 Read article