Efficient Image Geotagging Using Large Databases

Large image databases 1 Running head: LARGE IMAGE DATABASES Exploring human cognition using large image databases

Most cognitive psychology experiments evaluate models of human cognition using a relatively small, well-controlled set of stimuli. This approach stands in contrast to current work in neuroscience, perception, and computer vision, which have begun to focus on using large databases of natural images. We argue that natural images provide a powerful tool for characterizing the statistical environme...

Exploring Human Cognition Using Large Image Databases

Most cognitive psychology experiments evaluate models of human cognition using a relatively small, well-controlled set of stimuli. This approach stands in contrast to current work in neuroscience, perception, and computer vision, which have begun to focus on using large databases of natural images. We argue that natural images provide a powerful tool for characterizing the statistical environme...

Searching Large Image Databases using Color Information

The goal of this project is to implement an exploration system for large image databases in order to help the user find similar images to a query image in a very efficient method. The methods proposed in this system should be scalable to the largest databases currently in use; for example, www.google.com has an image search database via keywords search of about 1,000,000,000 images. While the p...

An Efficient Multi-filter Retrieval Framework For Large Image Databases

An efficient multi-filter retrieval framework for image retrieval in large image databases is proposed. Multiple filters are used to reduce the search ranges at different stages and thus save the time spent on unnecessary similarity comparison. First, a color label histogram filter uses a color label histogram with only thirteen bins to eliminate those images in the image database that are diss...

Efficient Exploration of Large Scientific Databases