您可以考虑的一个有效的方法是袋-of-Words模型。

A valid approach you can consider is the Bag-of-Words model.

基本上你可以做的目标图像脱机计算。您可以从这些图像中提取了一堆功能，以创建一个codebook与像 K-均值聚类算法一>。搜索最近的影像会导致如最近邻搜索的算法在的codebook空间中的应用

Basically you can do an offline computation of the target images. You can extract from those images a bunch of features in order to create a codebook with algorithms like k-means clustering. Searching for the nearest images will lead to the applications of an algorithm like Nearest neighbor search in the space of the codebook.

有关邻居搜索，您可以使用FLANN

For the neighbour search you can use FLANN

• http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN
• http://opencv.willowgarage.com/documentation/cpp/flann_fast_approximate_nearest_neighbor_search.html

• http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN
• http://opencv.willowgarage.com/documentation/cpp/flann_fast_approximate_nearest_neighbor_search.html

看看还在： 视觉相似性搜索算法

这只是一种可能性，真理必须被告知，这个话题实在是充满挑战和litterature它确实是巨大的。

This is only a possibility and, truth must be told, this topic is really challenging and litterature on it is really huge.

只是一些参考：

• http://www.cs.nott.ac.uk/~qiu/webpages/Papers/ColorPatternRecognition.pdf
• http://cs.brown.edu/~th/papers/Hofmann-UAI99.pdf
• http://www.ifp.illinois.edu/~jyang29/ScSPM.htm
• http://johnwinn.org/Publications/papers/Savarese_Winn_Criminisi_Correlatons_CVPR2006.pdf
• http://www-cvr.ai.uiuc.edu/ponce_grp/publication/paper/cvpr06b.pdf

• http://www.cs.nott.ac.uk/~qiu/webpages/Papers/ColorPatternRecognition.pdf
• http://cs.brown.edu/~th/papers/Hofmann-UAI99.pdf
• http://www.ifp.illinois.edu/~jyang29/ScSPM.htm
• http://johnwinn.org/Publications/papers/Savarese_Winn_Criminisi_Correlatons_CVPR2006.pdf
• http://www-cvr.ai.uiuc.edu/ponce_grp/publication/paper/cvpr06b.pdf