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Chinese Journal of Information on Traditional Chinese Medicine ; (12): 95-98, 2018.
Article in Chinese | WPRIM | ID: wpr-707000

ABSTRACT

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.

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