Your cart

Your Wishlist

Categories

📞 Working Hours: 9:30 AM to 6:30 PM (Mon-Sat) | +91 9739594609 | 🟢 WhatsApp

⏰ 9:30 AM - 6:30 PM |

Ensemble Approach Using Deep Learning And Transfer Learning In Classifying Diabetic Retinopathy
YouTube Video
Product Image
Product Preview

Multimodal biometric system based on Human signature and Palm Image

Category: BCA Projects

Price: ₹ 4500 ₹ 10000 55% OFF

Abstract:

This paper presents a multimodal biometric identification system based on the geometrical and palm print features of the human hand. The right hand images are acquired by a commercial scanner with a 150 dpi resolution. The geometrical features are obtained from the binarized images and consist on 15 measures. A support vector machines is used as verifier. The palm print texture is obtained by means of a 2D Gabor phase encoding scheme. A robust coordinate system is defined to make easier the image alignment. A Hamming distance and threshold are used for verifying the identity. A score and decision level fusion results have shown the improvement of the combined scheme

block-diagram

• Demo Video
• Complete project
• Full project report
• Source code
• Complete project support by online
• Life time access
• Execution Guidelines
• Immediate (Download)

Software Requirements:
1. Python 3.7 and Above
2. NumPy
3. OpenCV
4. Scikit-learn
5. TensorFlow
6. keras
Hardware Requirements:
1. PC or Laptop
2. 500GB HDD with 1 GB above RAM
3. Keyboard and mouse
4. Basic Graphis card

1. Immediate Download Online

Leave a Review

Only logged-in users can leave a review.

Customer Reviews

No reviews yet. Be the first to review this product!