关键词: 图像分割, 支持向量机, 视觉注意, 显著图

Abstract: An SVM（Support Vector Machine） model for the segmentation of color images of natural scenes based on visual attention is proposed.Based on human visual attention mechanism，the image is pre-divided，and saliency and non-saliency areas are obtained.The pre-divided image is further processed by some operators of morphology such that the training samples for SVM can be chosen and labeled automatically.The whole image is divided by SVM classifier.The proposed approach can solve the problem of uncertain boundary through effective information of the image based on visual attention mechanism.Combined with SVM，the approach can cut the image well without any priori knowledge and manual intervention.To evaluate the performance of the presented approach，some experiments on several images from the image dataset of University of California at Berkeley and Internet are accomplished.The experimental results demonstrate that not only the segmentations are consistent with the habits of the human visual attention，but also the proposed approach can obtain good segmentation results comparing with that of manual labeled.

Key words: image segmentation, support vector machine, visual attention, saliency map