Research On Automatic Feature Extraction For Medical Image

There is an enormous need for automatic feature extraction, and retrieval based on feature extraction in the growing field of digital archives. In particular, techniques of automatic feature extraction for medical image have been major topics of research in recent years.Automatic feature extraction for medical image is an key tecnique for fast diagnosis and CBIR( Content-based Image Retrieval ). The representative features, which are also invariant to the translation, scaling and rotation, should be select for improving the precision and velocitc.Wavelet transform is characterized by multi-resolution, which presents pyramid structure. It coincides well with the way by which people distinguish object from coarse to fineness and from large to tiny. The approach of linear moment convert the information of 2—D image into 1—D linear moment firstly and then transforms it with multi-resolution Orthonormal shell. Feature vector can be get through calculate the power of signal and the coefficients of the signal's FFT in different resolution.