Investigation of segmentation based pooling for image quantification

Reid Porter; Neal Harvey; Christy Ruggiero

doi:10.1117/12.2038707

7 March 2014 Investigation of segmentation based pooling for image quantification

Reid Porter, Neal Harvey, Christy Ruggiero

Proceedings Volume 9024, Image Processing: Machine Vision Applications VII; 90240F (2014) https://doi.org/10.1117/12.2038707
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States

Abstract

A key step in many image quantification solutions is feature pooling, where subsets of lower-level features are combined so that higher-level, more invariant predictions can be made. The pooling region, which defines the subsets, often has a fixed spatial size and geometry, but data-adaptive pooling regions have also been used. In this paper we investigate pooling strategies for the data-adaptive case and suggest a new framework for pooling that uses multiple sub-regions instead of a single region. We show that this framework can help represent the shape of the pooling region and also produce useful pairwise features for adjacent pooling regions. We demonstrate the utility of the framework in a number of classification tasks relevant to image quantification in digital microscopy.

Citation Download Citation

Reid Porter, Neal Harvey, and Christy Ruggiero "Investigation of segmentation based pooling for image quantification", Proc. SPIE 9024, Image Processing: Machine Vision Applications VII, 90240F (7 March 2014); https://doi.org/10.1117/12.2038707

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available