Recently, local features especially point descriptors have re- ceived lots of interest in the computer vision and image processing com- munities. SIFT and SURF descriptors have shown their powerful useful- ness on natural object recognition and classi cation. However, the use of local descriptors such as SIFT and SURF is still not very common in handwritten document image analysis now. In this paper, we propose an investigation on the description of handwriting by applying di erent interest points and local descriptors on historical handwritten images in the context of a coarse-to- ne segmentation-free word spotting method. The observation and analysis based on the experimental results can help optimizing the description of handwriting according to di erent applica- tions.