Phan, Thinh2024-08-062024-08-062024https://hdl.handle.net/10365/33911Ornithologist often need to recognize individual birds, but traditional invasive methods, such as capturing, marking, releasing, and recapturing of birds, have limitations. To overcome this, researchers use non-invasive alternatives, such as bird vocalizations. In our study, we used wing flap sounds of three male Zebra Finch birds for individual recognition. We achieved identification accuracies ranging from 55% to 100% by using a combination of Principal Component Analysis-K-Nearest Neighbor (PCA-KNN) and Cross-Correlation method on training data and testing data. PCA-KNN allows for dimensionality reduction and pattern recognition, while the Cross-Correlation method bases data analysis on shifting data elements. Our approach can be applied to other bird species and is becoming more accessible due to technological advancements. Non-invasive methods for bird identification are becoming increasingly popular, and our study demonstrates the potential for using wing flap sounds to recognize individual birds.NDSU policy 190.6.2https://www.ndsu.edu/fileadmin/policy/190.pdfIdentifying Individual BirdsK Nearest NeighborPrincipal Component AnalysisWing Flap Acoustic SignatureWing Flap SoundsThesis