menu
{ "item_title" : "Computational Algorithms for Fingerprint Recognition", "item_author" : [" Bir Bhanu", "Xuejun Tan "], "item_description" : "Fingerprints are the most established from of biometrics with the most promising future in real-world applications. However, because of the complex distortions among the different impressions of the same finger, fingerprint recognition is still a challenging problem. This book presents an entire range of novel computational algorithms for fingerprint recognition, all evaluated by the National Institute of Standards and Technology (NIST). These include feature extraction, indexing, matching, classification, and performance prediction/validation methods, which have been compared with state-of-art algorithms and found to be effective and efficient on real-world data. ", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/1/40/207/651/1402076517_b.jpg", "price_data" : { "retail_price" : "109.99", "online_price" : "109.99", "our_price" : "109.99", "club_price" : "109.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Computational Algorithms for Fingerprint Recognition|Bir Bhanu

Computational Algorithms for Fingerprint Recognition

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

Fingerprints are the most established from of biometrics with the most promising future in real-world applications. However, because of the complex distortions among the different impressions of the same finger, fingerprint recognition is still a challenging problem. This book presents an entire range of novel computational algorithms for fingerprint recognition, all evaluated by the National Institute of Standards and Technology (NIST). These include feature extraction, indexing, matching, classification, and performance prediction/validation methods, which have been compared with state-of-art algorithms and found to be effective and efficient on real-world data.

This item is Non-Returnable

Details

  • ISBN-13: 9781402076510
  • ISBN-10: 1402076517
  • Publisher: Springer
  • Publish Date: November 2003
  • Dimensions: 9.54 x 6.42 x 0.72 inches
  • Shipping Weight: 1.08 pounds
  • Page Count: 191

Related Categories

You May Also Like...

    1

BAM Customer Reviews