Seven Hu Moment Invariants for Images

This program computes the seven Hu moment invariants to extract shape characteristics from images, which can be effectively utilized for image retrieval and recognition tasks. By calculating these invariant moments through central moments normalization and nonlinear combinations, we obtain crucial information about image shapes, enabling more accurate and reliable image retrieval. The algorithm first computes raw image moments, then derives central moments, and finally applies Hu's seven invariant formulas to maintain consistency across geometric transformations. These moment invariants also serve in image classification tasks, helping distinguish between different image categories by comparing their shape descriptor vectors. Consequently, this implementation holds significant value for both research and practical applications in computer vision and image processing fields. Key functions include moment calculation, central moment normalization, and invariant feature vector generation.