Scene Classification with a Biologically Inspired Method

We present a biologically motivated method for scene image classification. The core of the method is to use shape based image property that is provided by a hierarchical feedforward model of the visual cortex [18]. Edge based and color based image properties are additionally used to improve the accu...

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Bibliographic Details
Main Author: Terashima, Yoshito
Other Authors: Tomaso Poggio
Published: 2009
Subjects:
Online Access:http://hdl.handle.net/1721.1/45516
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author Terashima, Yoshito
author2 Tomaso Poggio
author_facet Tomaso Poggio
Terashima, Yoshito
author_sort Terashima, Yoshito
collection MIT
description We present a biologically motivated method for scene image classification. The core of the method is to use shape based image property that is provided by a hierarchical feedforward model of the visual cortex [18]. Edge based and color based image properties are additionally used to improve the accuracy. The method consists of two stages of image analysis. In the first stage, each of three paths of classification uses each image property (i.e. shape, edge or color based features) independently. In the second stage, a single classifier assigns the category of an image based on the probability distributions of the first stage classifier outputs. Experiments show that the method boosts the classification accuracy over the shape based model. We demonstrate that this method achieves a high accuracy comparable to other reported methods on publicly available color image dataset.
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spelling mit-1721.1/455162019-04-11T00:32:20Z Scene Classification with a Biologically Inspired Method Terashima, Yoshito Tomaso Poggio Center for Biological and Computational Learning (CBCL) image classification vision We present a biologically motivated method for scene image classification. The core of the method is to use shape based image property that is provided by a hierarchical feedforward model of the visual cortex [18]. Edge based and color based image properties are additionally used to improve the accuracy. The method consists of two stages of image analysis. In the first stage, each of three paths of classification uses each image property (i.e. shape, edge or color based features) independently. In the second stage, a single classifier assigns the category of an image based on the probability distributions of the first stage classifier outputs. Experiments show that the method boosts the classification accuracy over the shape based model. We demonstrate that this method achieves a high accuracy comparable to other reported methods on publicly available color image dataset. 2009-05-11T17:30:10Z 2009-05-11T17:30:10Z 2009-05-10 http://hdl.handle.net/1721.1/45516 CBCL-277 MIT-CSAIL-TR-2009-020 8 p. application/pdf application/postscript
spellingShingle image classification
vision
Terashima, Yoshito
Scene Classification with a Biologically Inspired Method
title Scene Classification with a Biologically Inspired Method
title_full Scene Classification with a Biologically Inspired Method
title_fullStr Scene Classification with a Biologically Inspired Method
title_full_unstemmed Scene Classification with a Biologically Inspired Method
title_short Scene Classification with a Biologically Inspired Method
title_sort scene classification with a biologically inspired method
topic image classification
vision
url http://hdl.handle.net/1721.1/45516
work_keys_str_mv AT terashimayoshito sceneclassificationwithabiologicallyinspiredmethod