The proliferation of digital images creates problems for managing large image databases, indexing individual images, and protecting intellectual property. This paper introduces a novel image indexing technique that may be called an image hash function. The algorithm uses randomized signal processing strategies for a non-reversible compression of images into random binary strings, and is shown to be robust against image changes due to compression, geometric distortions, and other attacks. This algorithm brings to images a direct analog of Message Authentication Codes (MACs) from cryptography, in which a main goal is to make hash values on a set of distinct inputs pairwise independent. This minimizes the probability that two hash values collide, even when inputs are generated by an adversary.<\/p>\n","protected":false},"excerpt":{"rendered":"
The proliferation of digital images creates problems for managing large image databases, indexing individual images, and protecting intellectual property. This paper introduces a novel image indexing technique that may be called an image hash function. The algorithm uses randomized signal processing strategies for a non-reversible compression of images into random binary strings, and is shown […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13558],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-155763","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-security-privacy-cryptography","msr-locale-en_us"],"msr_publishername":"","msr_edition":"IEEE International Conference on Image Processing: ICIP 2000","msr_affiliation":"","msr_published_date":"2000-09-01","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"210932","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"venkie00robust.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/venkie00robust.pdf","id":210932,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":210932,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/venkie00robust.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"venkie","user_id":34544,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=venkie"},{"type":"text","value":"S.-M. 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