MATLAB-Based Fingerprint Recognition System

Application Background This is a texture analysis-based fingerprint recognition system implemented using MATLAB. The program interface displays as follows: Input images must strictly adhere to 256x256 pixel dimensions, 8-bit grayscale format, and 500dpi resolution for fingerprint data. If these specifications are not satisfied, appropriate adjustments must be made to relevant function parameters. To run the program in MATLAB, set the current directory as the working directory and enter "fpextractdemo" in the command line interface. Key technologies implemented include: - Fingerprint image field computations: The system calculates intensity fields using pixel value analysis, gradient fields through Sobel or Prewitt operators, orientation fields via gradient-based methods like least squares estimation, and frequency fields employing Fourier transform or wavelet analysis - Image segmentation: Implemented using thresholding techniques (Otsu's method) or region-based approaches to isolate fingerprint regions from background - Image enhancement: Utilizes histogram equalization for contrast improvement and adaptive filtering techniques for noise reduction - Image convergence: Implements iterative algorithms to enhance ridge clarity and minimize background interference - Image smoothing: Applies Gaussian or median filters to reduce noise while preserving ridge structures - Image enhancement: Employs Gabor filter banks or directional filters to enhance ridge-valley patterns for improved feature extraction These core components form the fundamental processing pipeline of the fingerprint recognition system.