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Chinese herbal medicine plant picture retrieval method based on multi-feature fusion BOW model

A technology of multi-feature fusion and Chinese herbal medicine, applied in special data processing applications, instruments, electronic digital data processing, etc., can solve the problems of difficult image retrieval of Chinese herbal medicine plants

Active Publication Date: 2016-07-27
ZHEJIANG UNIV
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Problems solved by technology

At the same time, due to the large number of Chinese herbal plant species and the diversity among them, the retrieval of Chinese herbal plant images is becoming more and more difficult.

Method used

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  • Chinese herbal medicine plant picture retrieval method based on multi-feature fusion BOW model
  • Chinese herbal medicine plant picture retrieval method based on multi-feature fusion BOW model
  • Chinese herbal medicine plant picture retrieval method based on multi-feature fusion BOW model

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[0069] Such as figure 1 Shown, the present invention a kind of Chinese herbal medicine plant picture retrieval method based on the BOW model of multi-feature fusion. In this embodiment, steps that are not described in detail, such as steps 2)-6), are specifically performed as described in the foregoing specific implementation manners. The main steps adopted in this embodiment are as follows:

[0070] 1) Normalize the size of the Chinese herbal medicine plant picture, first normalize the longer side of the picture to 480 pixels, and then scale the shorter side to the corresponding pixel according to the aspect ratio of the original picture;

[0071] 2) The normalized image obtained in step 1) is densely sampled with a step size of 4 and an image block size of 16×16 pixels, extracting SIFT features and OpponentSIFT features for each sampled image block, and splicing and merging them into A vector to obtain the local feature vector of each image block;

[0072] 3) Randomly sel...

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Abstract

The invention discloses a Chinese herbal medicine plant picture retrieval method based on a multi-feature fusion BOW (Bag-of-Words) model. The method comprises the following steps of firstly, performing normalization processing on the dimension of Chinese herbal medicine pictures; then, extracting SIFT (Scale-invariant Feature Transform) features and Opponent SIFT features based on dense sampling on the Chinese herbal medicine pictures subjected to normalization processing; then, clustering the features extracted in the former step by a k-means clustering algorithm to obtain a visual dictionary, wherein the clustering center is a visual word; next, expressing the visual word in the visual dictionary for local features by local linear code to obtain a corresponding coding vector; then, performing pooling processing on the code vector corresponding to local features of the Chinese herbal medicine pictures by using a maximum value pooling method to obtain picture features; and finally, inputting the picture features into a trained SVM (Support Vector Machine) classifier to obtain corresponding categories; and returning the pictures in the corresponding categories to a user.

Description

technical field [0001] The invention relates to a method for retrieving pictures of Chinese herbal medicine plants, in particular to a method for retrieving pictures of Chinese herbal medicine plants based on a multi-feature fusion BOW model. Background technique [0002] Traditional Chinese medicine is an important part of the treasure house of traditional Chinese culture, and the revival of Chinese medicine culture is an important part of realizing the revival of Chinese culture. The construction of a professional Chinese herbal medicine plant image retrieval system will help promote the promotion and promotion of traditional Chinese medicine. Popularity, because it can lower the threshold for people to know and understand traditional Chinese medicine, give people a visual and intuitive cognition through image data, and arouse people's strong interest in traditional Chinese medicine culture. However, due to the differences in illumination, viewing angle and size of Chinese...

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/5838
Inventor 张引魏宝刚庄越挺谭亮
Owner ZHEJIANG UNIV
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