In recent years, computer vision community has devoted efforts on the recognition of basic-level categories. On the other hand, finegrained object recognition which targets at recognizing objects belonging to the same basic-level class, is a more challenging problem and receives an increasing attention during recent years. In this paper, we propose a hierarchical structure Category-Separating Strategy for branded handbag recognition which is the first attempt to address the fine-grained object recognition on branded handbags. Experimental results on a newly constructed dataset are provided to show the effectiveness of the proposed methodology.