Skip to main content

Content-based image search

Project description

About

ricerca is a python package for content-based searching of microscope images. It uses a set of numerical features to describe each image and a method for combining them to measure similarity.

For more information about ricerca, please visit http://murphylab.web.cmu.edu/software/ricerca/

Authors

Ivan Cao-Berg, Baek Hwan Cho, Jennifer Bakal and Robert F. Murphy
Lane Center for Computational Biology
School of Computer Science
Carnegie Mellon University

References

  • B.H. Cho, I. Cao-Berg, J.A. Bakal, and R.F. Murphy (2012) OMERO.searcher: Content-based image search for microscope images. Nature Methods 9:633-634.
  • Leejay Wu, Christos Faloutsos, Katia P. Sycara, and Terry R. Payne. 2000. FALCON: Feedback Adaptive Loop for Content-Based Retrieval. In Proceedings of the 26th International Conference on Very Large Data Bases (VLDB ‘00), Amr El Abbadi, Michael L. Brodie, Sharma Chakravarthy, Umeshwar Dayal, Nabil Kamel, Gunter Schlageter, and Kyu-Young Whang (Eds.). Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 297-306.

Project details


Release history Release notifications

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
ricerca-1.1.3.tar.gz (17.8 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page