Fourier Band Brightness Descriptor Program for Extracting Image Shape Features

This document presents a methodology for developing a Fourier transform-based algorithm designed to extract shape features from digital images. The core algorithm employs Fourier analysis to examine luminance variations within images, leveraging this information to characterize object shapes. Implementation requires converting input images to grayscale format, followed by applying Fourier transformation to decompose images into frequency components. Key computational steps include calculating magnitude and phase spectra for each frequency component to derive shape descriptors. The implementation framework involves: initial image preprocessing using RGB-to-grayscale conversion, 2D FFT application for spatial-to-frequency domain transformation, magnitude spectrum calculation via abs() functions, and phase extraction using angle() operations. A practical demonstration includes complete MATLAB/Python code structure and application to sample images to validate the algorithm's shape discrimination capabilities.