Among various image retrieval approaches, the use of sketches lets one express a precise visual query with simple and widespread means. The challenge consists in finding a content representation that allows you to effectively compare sketches and images, while supporting efficient retrieval in order to make the system scalable. We put forward a sketch-based image retrieval solution where sketches and natural image contours are represented and compared in the wavelet domain. The relevant information regarding query sketches and image content has, thus, a compact representation that can be readily employed by an efficient index for retrieval by similarity. Furthermore, with this solution, the balance between effectiveness and efficiency can be easily modified in order to adapt to the available resources. A comparative evaluation with a state-of-the-art method on the Paris dataset and a subset with 535K images of the Image Net dataset shows that our solution can preserve effectiveness while being more than one order of magnitude faster.