In this paper, we presented an image search service for mobile users. It can be used to acquire related information by taking and sending pictures to the server, for example, getting book reviews by a photo of the cover. The key problem here is to find images that contain the same prominent object as that in the query image. In the literature, local feature based image matching has been proven to outperform those based on global features. When using local features, however, one query image may contain thousands of high dimensional feature vectors. Each feature vector needs to match against millions of features in the database. Therefore, it is critical to design an efficient search scheme. Our proposed matching approach was based on identifying semi-local visual parts from multiple query images. Experiments on two real-world datasets showed that this approach was superior to conventional solutions.