Scalable Arrow Detection in Biomedical Images

In this paper, we present a scalable arrow detection technique for biomedical images to support information retrieval systems under the purview of content-based image retrieval (CBIR) and text information retrieval (TIR). The idea primarily follows the criteria based on the geometric properties of the arrow, where we introduce signatures from key points associated with it. To handle this, images are first binarized via a fuzzy binarization tool and several regions of interest are labeled accordingly. Each region is used to generate signatures and then compared with the theoretical ones to check their similarity. Our validation over biomedical images shows the advantage of the technique over the most prominent state-of-the-art methods.