基于SURF改进算法的工件识别
Workpiece recognition based on SURF improved algorithms
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摘要: 针对SURF算法容易出现误匹配等情况, 提出一种基于SURF算法的改进算法。该方法首先利用SURF算法中Hessian矩阵检测特征点, 然后在特征匹配时利用欧氏距离进行双向匹配, 最后利用改进RANSAC算法假设精确特征点对的数学模型, 找到符合数学模型的"内点", 从而提高特征匹配的精度。目的在于提高工件识别的效率。用工件图片对本文算法有效性进行检验, 结果表明, 算法能够更准确、高效地识别工件。Abstract: The workpiece identification method (WIM) based on improved SURF algorithm is proposed against the SURF which prone to match wrongly. The method first apply the Hessian matrix of SURF to detect feature points. Then, the Euclidean distance is utilized to match. Finally, the improved RANSAC algorithm is used to assume the exact feature point pair mathematical model, and find the "inner point" that conforms to the mathematical model, so as to improve the accuracy of feature matching. The purpose is to improve the efficiency of workpiece recognition in the industry. Therefore, the effectiveness of the proposed algorithm is verified by the workpiece image. The results show that workpiece can be identified more accurately and efficiently through the proposed method.
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