During my internship at S4DS, I contributed to a project focused on Topological fingerprint analysis. My key responsibilities included:Fingerprint Data Acquisition:Obtained Synthetic Fingerprint Data from Anguli DatasetObtained fingerprint data provided by KEM, ensuring the data was formatted and ready for subsequent analysis.Implementation of the Segment Anything Model (SAM):Applied the Segment Anything Model (SAM) to efficiently separate and isolate each individual fingerprint from the provided images, enhancing the accuracy of downstream analysis.Semantic Sketching:Performed semantic sketching on segmented fingerprints to enhance their visual representation, aiding in better feature recognition and analysis.Minutiae Points Extraction:Identified and extracted minutiae points (specific ridge characteristics) from each fingerprint, crucial for detailed fingerprint analysis and comparison.Topological Data Analysis:Conducted topological data analysis, including the generation of persistence barcodes, to visualize and characterize the topological structures of the fingerprints. This involved examining the spatial relationships and structures within the fingerprint data.Distance Matrix Calculation:Calculated the distance matrix for the persistence barcodes of all ten fingerprints of each patient, providing a quantitative measure for comparing the topological features across fingerprints.This experience allowed me to apply and enhance my skills in data analysis, machine learning, and topological data analysis, contributing to fingerprint identification and characterization advancements.