长白山野生中草药植物图像检索方法研究

Research on Image Retrieval Method of Wild Chinese Herbal Medicine Plants in Changbai Mountain

目的研究基于视觉词袋的图像检索方法并应用于长白山中草药植物图像检索领域。方法采用SURF算法提取图像视觉特征,稀疏编码方法构造视觉词典,并提出支持向量机(SVM)和近似最近邻(ANN)相结合的改进方法完成分类器分类训练。结果选取2500张中草药图像作为检索样本,在视觉单词数量为500的情况下,平均检索时间为481 ms,平均查准率为88.95%。结论本方法能有效提高图像检索效率与准确度,同时表现出较好的鲁棒性。

Objective To study the visual word bag based image retrieval method and apply it in the field of image retrieval of wild Chinese herbal medicine plants in Changbai Mountain. Methods SURF operator was used to extract visual features. Then sparse coding method was used to structure visual dictionary. The classifier was trained by combination of support vector machine （SVM） and approximate nearest neighbors （ANN） method. Results Totally 2500 photos of Chinese herbal medicine plants were chosen. When the visual word number was 500, the average retrieval time was 481 ms, and the average query accuracy was 88.95%. Conclusion The method can effectively improve the efficiency and accuracy of image retrieval, and has better robust.