Books image retrieval is an important application of CBIR (content-based image retrieval). SIFT(scale inva-riant feature transform) and HOG(histogram of oriented gradient) are widely used in CBIR and object recognition. A book image is divided into nine blocks called sub-images according to its characteristics. We extract features from the image based on SIFT

and then we combine the features with the HOG feature to create a combined feature. The combined feature occupies little data and describes an image well. We use a new way to calculate the combined features’ similarity

which will avoid large errors caused by some sub-image. An image set with 50000 book images is used to test our method and we find the accuracy to be acceptable and the time consumed by the retrieval process is quite short.