Multi-Feature Bio-Inspired Model for Scene Classification

Abstract:

A multi-feature bio-inspired model for scene image classification (MFBIM) is presented in this work; it extends the hierarchical feedforward model of the visual cortex. Firstly, each of three paths of classification uses each image property (i.e. shape, edge or color based features) independently. Then, BPNN assigns the category of an image based on the previous outputs. Experiments show that the model boosts the classification accuracy over the shape based model. Meanwhile, the proposed approach achieves a high accuracy comparable to other reported methods on publicly available color image dataset.

• Periodical: Applied Mechanics and Materials (Volumes 303-306)
• Pages: 1569-1572
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.303-306.1569
• Online since: February 2013
• Authors: De Kun Hu, Jie Lin
• Keywords: Bio-Inspired Model, Computer Vision, Scene Classification

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