Historical documents are essentially formed of handwritten texts that exhibit a variety of perceptual environment complexities. The cursive and connected nature of text lines on one hand and the presence of artefacts and noise on the other hand hinder achieving plausible results using current image processing algorithm. In this paper, we present a new algorithm which we termed QTE (Query by Text Example) that allows for training-free and binarisation-free pattern spotting in scanned handwritten historical documents. Our algorithm gives promising results on a subset of our database revealing ∌83% success rate in locating word patterns supplied by the user.