Phase singularities (PSs) refer to the zero points in complex signals. In previous studies, we found that PSs can provide rich information for image representation and are robust to image transformation, noise etc. This paper makes use of PS and bag of visual words (BoVW) model to construct bag of PS representation for images. Then we use SVM to classify bag of PS representations. Compared with previous works using SIFT points, our new representations not only use more interested points, but also allow us to pre-classify the words according to the sign property of PSs. The experimental results show that the proposed methods achieve better performance on PASCAL2005 image classification tasks than SIFT detectors.