Hierarchical system for content based categorization and orientation of consumer images

Gaurav Sharma, Abhinav Dhall, Santanu Chaudhury, Rajen Bhatt

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review


A hierarchical framework to perform automatic categorization and reorientation of consumer images based on their content is presented. Sometimes the consumer rotates the camera while taking the photographs but the user has to later correct the orientation manually. The present system works in such cases; it first categorizes consumer images in a rotation invariant fashion and then detects their correct orientation. It is designed to be fast, using only low level color and edge features. A recently proposed information theoretic feature selection method is used to find most discriminant subset of features and also to reduce the dimension of feature space. Learning methods are used to categorize and detect the correct orientation of consumer images. Results are presented on a collection of about 7000 consumer images, collected by an independent testing team, from the internet and personal image collections.

Original languageEnglish
Title of host publicationPattern Recognition and Machine Intelligence - Third International Conference, PReMI 2009, Proceedings
Number of pages6
Publication statusPublished - 1 Dec 2009
Externally publishedYes
Event3rd International Conference on Pattern Recognition and Machine Intelligence, PReMI 2009 - New Delhi, India
Duration: 16 Dec 200920 Dec 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5909 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference3rd International Conference on Pattern Recognition and Machine Intelligence, PReMI 2009
CityNew Delhi

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