Hu Moment-contour matching

These seven immutations constitute a set of feature quantities. hu. M. K proved in 1962 that they have rotation, scaling, and moving immutability.

In fact, in the process of recognizing objects in images, only M1 and M2 are well-preserved, while other immutations produce large errors, some scholars believe that only the immutations based on the second moment can describe two-dimensional objects with real rotation, scaling, and shift immutability (M1 and M2 are exactly composed of the second moment ). However, I have not proved whether it is true or not.

The feature quantity composed of Hu moments identifies images. The advantage is that the image recognition speed is fast. The disadvantage is that the recognition rate is low. I have done Gesture Recognition and the recognition rate is about 30% for the split gesture profile, for images with rich textures, the recognition rate is even worse, with only around 10%. This is due to the fact that Hu Moment immutations only use low-order moments (at most, third-order moments), and the image details are not well described, resulting in incomplete descriptions of the image.

Hu moments are generally used to recognize large objects in an image. They describe the shape of an object, and the texture features of the image cannot be too complex. The image recognizes the shape of a fruit, or the recognition of simple characters in the license plate will be better.

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