Cell image classification using histograms, higher order statistics and adaboost

Chandran, Vinod, Banks, Jasmine, Boles, Wageeh, Chen, Brenden, & Tomeo-Reyes, Inmaculada (2013) Cell image classification using histograms, higher order statistics and adaboost. In The 20th IEEE International Conference on Image Processing (ICIP) - International Competition on Cells Classification by Fluorescent Image Analysis, 15 - 18 September 2013, Melbourne, Australia.

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A cell classification algorithm that uses first, second and third order statistics of pixel intensity distributions over pre-defined regions is implemented and evaluated. A cell image is segmented into 6 regions extending from a boundary layer to an inner circle. First, second and third order statistical features are extracted from histograms of pixel intensities in these regions. Third order statistical features used are one-dimensional bispectral invariants. 108 features were considered as candidates for Adaboost based fusion. The best 10 stage fused classifier was selected for each class and a decision tree constructed for the 6-class problem. The classifier is robust, accurate and fast by design.

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ID Code: 68693
Item Type: Conference Item (Presentation)
Refereed: No
Additional URLs:
Keywords: Cell, Classification, Histogram, Bispectrum, Higher order statistics, Adaboost
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 IEEE
Deposited On: 17 Mar 2014 23:37
Last Modified: 29 Apr 2014 06:12

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