The invention discloses a multi-
feature fusion image retrieval method. The method comprises the steps of firstly, inputting an image I to be retrieved; secondly, constructing a color
feature vector and a SIFT
feature vector of the image I; thirdly, training the image in a query image
library to obtain a color feature dictionary and a SIFI feature dictionary, and using a
visual word for representing the image in the image
library; fourthly, using the
visual word for representing the image I, calling a
candidate image set Q from the query image
library according to the
visual word, and calculating a similarity value
score (Q,I); fifthly, selecting a local area Si with the
visual saliency in the image I and repeatedly executing the step three and the step four to obtain a
candidate image set K, and calculating a similarity value
score<sal>(K,I); sixthly, using an overlapped image set of the two candidate fusion sets as D, fusing
score<sal>(D,I) and score (D,I), and calculating a final similarity value score<*>(D,I); seventhly, using the image with the highest final similarity value as a
retrieval result of the image I to be retrieved. The multi-
feature fusion image retrieval method has the advantages of lowering
image noise and improving the retrieval accuracy.