Feature Extraction Based on Wavelet Transform and Moment Invariants for Medical Image

Abstract

The objective of feature extraction is to decrease the original data set by measuring definite features, or properties, which recognizes one input pattern from another.The main idea of the proposed system depends on the feature extraction where the system uses two phases the first phase discrete wavelet transform and the second phase seven moment’s invariants. In this paper apply two level discrete wavelet transform of medical image; obtain seven bands of texture features are extracted from wavelet coefficients and then apply seven moments invariant for each band where obtain 49 features for each medical image. The proposed system was implemented on a real human MRI dataset, some of them were obtained from the hospitals and the other was obtained from the dataset (Brain-Tumor-Progression), available on the Internet and the proposed system implemented in programing language Visual Basic 6.0.