The use of a person's fingerprints as a method of identification is both one of the earliest methods and one of the most common methods used today. The process of recognising a person's fingerprints can be broken down into two primary groups: image-based and minutiae-based. An approach to fingerprint identification that is based on photographs is provided in this piece of research. After finding the central point and finishing the pre-processing of the image, the next step is feature extraction, which can be done with the help of a variety of different methods, including the Fast Fourier Transform (FFT), the Discrete Cosine Transform (DCT), the Discrete Wavelet Transform (DWT), and the Gabor Filter. This list is comprised of the mean energy, the standard deviation, and the Shannon entropy. In this study, a comparison of all four transforms reveals that the DCT and DFT are more effective than the DWT and the Gabor filter.