• Maheswara
• A Krishna mohan

In recent times, automatic biometric authentication has emerged as the backbone of the new-age solutions to our society’s ever increasing demand of improved security requirements. Palmprint recognition is a promising biometric system for forensic and commercial applications. The proposed work provides a novel technique for features extraction phase by using Speed Up Robust Features (SURF) algorithm, then 2D principal component analysis (2D PCA) and 2D linear discriminant analysis (2D LDA) are used for dimensionality reduction. Deep convolutional neural network is used for classification. The algorithms have been tested by using palmprint database. The recognition accuracy of the proposed approach with some existing approaches is taken. The simulation results show that the proposed approach gives good and comparable results with some other approaches.

Palm printing, SURF, Deep convolution neural network, palm print recognition.

"PERSONAL IDENTIFICATION BASED ON PALM PRINT IMAGES USING DCNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 8, page no.443-447, August-2018, Available :http://www.jetir.org/papers/JETIR1808063.pdf

"PERSONAL IDENTIFICATION BASED ON PALM PRINT IMAGES USING DCNN", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 8, page no. pp443-447, August-2018, Available at : http://www.jetir.org/papers/JETIR1808063.pdf