| Popis: |
Nowadays, an enormous number of photographic images are uploaded on the Internet by casual users. In this study, we consider the concept of embedding geographical identification of locations as geotags in images. We attempt to retrieve images having certain similarities (or identical objects) from a geotagged image dataset. We then define the images having identical objects as orthologous images. Using content-based image retrieval (CBIR), we propose a ranking function--orthologous identity function (OIF)--to estimate the degree to which two images contain similarities in the form of identical objects; OIF is a similarity rating function that uses the geographic distance and image distance of photographs. Further, we evaluate the OIF as a ranking function by calculating the mean reciprocal rank (MRR) using our experimental dataset. The results reveal that the OIF can improve the efficiency of retrieving orthologous images as compared to using only geographic distance or image distance. |
