In this paper, we propose a novel image search scheme, contextual image search. Different from conventional image search schemes that present a separate interface (e.g., text input box) to allow users to submit a query, the new search scheme enables users to search images by only masking a few words when they are reading through Web pages or other documents. Rather than merely making use of the explicit query input that is often not sufficient to express the search intent, our approach explores the context information to better understand the search intent, and expects to obtain better search results, through two key ways: query augmenting and search results reranking using context. To the best of our knowledge, this is the first attempt to conduct image search with both textual and visual context. Beyond contextual Web search, the context in our case is much richer and includes images besides texts. Experiments show that the proposed scheme makes image search more convenient and the search results are more relevant to user intention.