An improved FastICA algorithm and its application in image feature extraction

There are most important features hiding in the higher-order statistics information of the images. They are extracted by classical fast-fixed independent component analysis (FastICA algorithm) which requires a large amount of calculation and it is sensitive on the selection of initial point. To overcome the two shortcomings, an improved FastICA algorithm is proposed and mathematical models are constructed. And they are applied to obtain the basic vectors from the images. Finally, take litchi fruit image in natural environment as an instance and experiment with Matlab software. The results show that there are less computation and stronger stability of the improved FashICA algorithm used to extract image features.