• Parneet kaur
• Komal sood

Nowadays, MMB (multimodal biometric) system has currently increased concern because of its capability for reducing particular intrinsic challenges of the SBM (single biometric modalities) as well as for enhancing the complete identification rate and time consumption. The basic BRS (biometric recognition system) comprises processing, FE (feature extraction), FS (feature selection), SLF (score level fusion), classification modules. The vigour of the MMB system is based on and more reliable to extract unique data from the SBTs (single biometric traits). This research model designed a novel AL-CNN method for MMBS (multimodal biometric system) by utilizing iris-facial traits. The iris and facial traits FE (feature extraction) are extracted utilizing an effective MR (multi-resolution) GF (Gabor Filter) to filter the text data in various orientations and scales. In this analysis, the KPCA algorithm is developed to extract the feature vectors or unique feature sets. The SLF (score level fusion) procedure of valuable feature sets from two extracted feature sets is merged at hybridization AL-CNN model. It has implemented the novel approach to calculate the valuable FVs (feature vectors) and classified the features. The simulation procedure is evaluated on FERET for face and CASIA v3 for iris image data set. The experiment results from analyses has improved the recognition rate of 97.97 per cent, time consumption 1.2 sec, mitigate the error rate, and compared with the existing method (FK-NN).

: MMBS (multimodal biometric system), KPCA (kernel principal component analysis), FK-NN (Fuzzy K nearest neighbour), and AL-CNN (ant lion- convolutional neural network)

"FACIAL-IRIS AUTOMATIC MULTIMODAL BIOMETRIC IDENTIFICATION SYSTEM USING AL-CNN METHOD", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 4, page no.761-769, April-2021, Available :http://www.jetir.org/papers/JETIR2104303.pdf

"FACIAL-IRIS AUTOMATIC MULTIMODAL BIOMETRIC IDENTIFICATION SYSTEM USING AL-CNN METHOD", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 4, page no. pp761-769, April-2021, Available at : http://www.jetir.org/papers/JETIR2104303.pdf