Criminal Investigation Using Deep Learning and Image Processing
Ossama H. Embarak, Maryam J. Almesmari, Fatima R. Aldarmaki, Maryam Alameeri · 2024
This book chapter focuses on the application of deep learning algorithms to address critical security concerns related to identifying fake currency, verifying handwritten signatures, and detecting real and fake facial expressions. These concerns pose a threat to the security of private and government sectors in multiple countries, including the UAE. The chapter highlights the effectiveness of automated methods that incorporate machine learning and image processing in identifying these security issues with high accuracy levels of up to 99%. Image analysis plays a crucial role in accessing essential case clues and evidence that can aid public security organizations in solving cases. As technology advances, fuzzy image processing becomes an indispensable tool in criminal investigations and other areas of public security. Therefore, it is crucial to address specific issues to effectively prevent and investigate crimes, and the utilization of deep learning algorithms offers a promising approach to addressing these concerns. Therefore, specific issues need to be addressed to stop and investigate crime effectively, and the use of deep learning algorithms offers a promising approach to addressing these concerns.