Abstract
With the rapid development of information technology, the sizes of digital libraries become larger and larger. How to quickly and effectively search the desired images in huge digital libraries becomes the challenge needed to resolve with high priority. In this study, we firstly propose two motif-based matrices, i.e., the motif average matrix (MAM) and motif excessive matrix (MEM), to describe the color and texture features of an image. Subsequently, in terms of the inference of MAM and MEM, a motif matrix (MM) is further proposed to index rotated images and resolve the issue of rotated image retrieval. That is, in the light of such an inference, MM incorporates the color and texture characters and reveals the consistent relevance between the original and rotated images, which can be effectively used for rotated image retrieval. To extensively test the performance of our method, we carry out the experiments on the benchmark Corel image dataset, Brodatz texture image dataset, WIPO global brand dataset, and the experimental results show that our approach of motif matrix inference improves the retrieval performance in comparison with the state-of-the-art image retrieval approaches.
Highlights
In recent years, with the rapid development of multimedia and computer technologies, the sizes of digital libraries become larger and larger
4 Results and discussion we implement our approach of motif matrix inference (MMI) for image retrieval on Corel image dataset [38,39,40], Brodatz texture image dataset [20, 41, 42], and WIPO global brand dataset [43, 44], which are three most widely adopted benchmark datasets in the literatures of content-based image retrieval (CBIR) and trademark search
motif average matrix (MAM) and motif excessive matrix (MEM) are further mapped to motif matrix (MM) to resolve the issues of rotated image retrieval
Summary
With the rapid development of multimedia and computer technologies, the sizes of digital libraries become larger and larger. In these large digital libraries, how to find desired image information, especially for numerous rotate images, has become a challenge needed to resolve urgently. As the number of trademark images is increasing rapidly in trademark registration system, the design of new patterns should prevent the conflict to the similar trademarks registered. The similar patterns caused by rotation need to be effectively avoided. Trademark image retrieval system can find similar trademarks immediately after entering a new trademark image for registration, which can effectively protect the legitimate rights and interests of registered trademarks. Image retrieval has become a research hot spot
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