BinancePy: Python - Powered Crypto Trading
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Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
NHCE
Abstract
Fingerprint images in crime scene are important clues to solve serial cases. Crime scene
fingerprint identification system using deep machine learning with Convolutional Neural
Network (CNN). Images are acquired from crime scene using methods ranging from precision
photography to complex physical and chemical processing techniques and saved as the
database. The images collected from the crime scene are usually incomplete and hence
difficult to categorize. The fingerprint recognition system is divided into three stages that are
fingerprint image pre-processing, feature extraction and matching. Suitable enhancement
methods are required for pre-processing the fingerprint images. The output of this stage will
be passed to feature extraction stage which is extract the minutiae point (ridge ending,
Bifurcation) from thinning fingerprint image, then the false minutiae removal is applied to
extract real minutiae. The features of pre- processed data are fed into the CNN as input to
train and test the network.