Deformed trademark retrieval based on 2D pseudo-hidden Markov model

Abstract

A new deformed trademark retrieval method based on two-dimensional pseudo-hidden Markov model (2D PHMM) is proposed in this paper. Most trademark retrieval systems focus on color features, shape silhouettes, or the combination of color and shape. However, these approaches adopted individual silhouettes as shape features, leading to the following two crucial problems. First, most trademarks have various numbers of decomposed components, while the silhouette-based approaches cannot handle the variety correctly. Second, the infringement cases in which trademarks are changed by non-rigid deformation, in particular nonlinear deformation, may escape detection. Thus, our method focuses on the overall appearance of trademarks and incorporates color and shape features into 2D PHMM to tackle the above two problems. The reason to involve 2D PHMM is that it has high tolerance to noise and distortion, moreover, contextual information can be incorporated into it in a natural and elegant way. However, 2D PHMM is computation intensive and sensitive to rotation, scale and translation variations. Thus, it is the main originality of this paper to include the advantages of 2D PHMM but to exclude its disadvantages. As a result, similar trademarks can be retrieved effectively, even those with different numbers of components or non-rigid deformation. Various experiments have been conducted on a trademark database to prove the effectiveness and practicability of the proposed method.