Abstract
According to high development of digital technologies, image processing is more and more import in various fields, such as robot navigator, images classifier. Current image processing model still need large amount of training data to tune processing model and can’t process large images effectively. The recognition successful rate was still not very satisfied. Therefore, this paper researched saliency prior based image processing model, present the Gaussian mixture process and design the feature point based classifier, and then evaluate the model by supervised learning process. Finally, a set of experiments were designed to demonstrate the effectiveness of this paper designed saliency prior based image processing model. The result shows the model works well with a better performance in accurate classification and lower time consumption
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