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Image Feature Extraction Based on Support Vector Machine and Multi-DSP Combined Structure

机译:基于支持向量机和多DSP组合结构的图像特征提取

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An image feature extraction method based on support vector machine (SVM) is presented in this paper, which first seeks the optimal separating hyperplane in small samples and then projects image data in the corresponding normal direction. In multiclass cases, the method has an optimal choose for selecting projecting axis by some sub-SVMs with simplified structure. A multi- DSP combined structure system has been designed to implement this method by TMS320DM648 and TMS320DM6446. The results show the proposed method is effective, and also meets the real-time requirement.
机译:本文提出了一种基于支持向量机(SVM)的图像特征提取方法,该方法首先在小型样本中寻找最佳分离超平面,然后在相应的正常方向上投射图像数据。在多种子体情况下,该方法具有最佳选择,用于通过简化结构选择一些子SVM的投影轴。多DSP组合结构系统旨在通过TMS320DM648和TMS320DM6446实现该方法。结果表明,所提出的方法是有效的,并且还满足了实时要求。

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