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Segmentation Tree Based Multiple Object Image Retrieval

Inaccurate image segmentation often has a negative impact on object-based image retrieval. Researchers have attempted to alleviate this problem by using hierarchical image representation. However, these attempts suffer from the inefficiency in building the hierarchical image representation and the high computational complexity in matching two hierarchically represented images. Existing approaches construct the hierarchical image representation in two steps. The first step is to perform segmentation at different image resolutions, and the second step is to construct a hierarchical representation of the image by associating segments from different resolutions. In this research, an innovative all-in-one run approach is proposed that concurrently performs image segmentation and hierarchical tree construction, producing a hierarchical region tree to represent the image. In addition, an efficient hierarchical region tree matching algorithm is proposed with a reasonably low time complexity and used in multiple object image retrieval. The experimental results demonstrate the efficacy and efficiency of the proposed approach.