Sorted dominant local color for searching large and heterogeneous image databases

Recent work on Content-Based Image Retrieval (CBIR) have presented alternative methods for fast image indexing and retrieval using Bags of Visual Words (BoVW). In such methods, images are represented as sets of visual words, which can be indexed and searched using well-known text retrieval techniques, allowing fast search on large image databases. In this paper we propose a novel method based on BoVW that improves over current methods by using a new kind of local color descriptor, which we call SDLC, that encodes the most predominant color occurrences in blocks of different image regions. We report results of experiments we performed with two publicly available image databases. The results indicate that the use of SDLC led to a quite competitive CBIR method in comparison to the state-of-the-art.