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Image classification in natural scenes: Are a few selective spectral channels sufficient?

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Presentation on theme: "Image classification in natural scenes: Are a few selective spectral channels sufficient?"— Presentation transcript:

1 Image classification in natural scenes: Are a few selective spectral channels sufficient?

2 Common cameras capture three (wideband) spectral channels – Red, Green, Blue Ignore information outside of the visible spectrum Rich Spectral Information in Natural Scenes

3 Visible NIR Wavelength (nm)

4 Rich Spectral Information in Natural Scenes Hyperspectral imaging gives detailed spectral profiles for each pixel

5 Rich Spectral Information in Natural Scenes Hyperspectral imaging gives detailed spectral profiles for each pixel

6 Capturing 325 bands requires specialized equipment – Costly, heavy, low SNR – Needs dedicated computer interface What if we can get similar performance from only a few bands? – We find that using 6 bands is as good as using 325 Which bands to choose? Can we also increase SNR? Reducing Dimensionality of Data Capture

7 Improving classification accuracy RGB + NIR 6 bandpass filters Train SVM classifiers to identify 7 classes of material in natural scenes: Vegetation, Metal, Concrete, Pathway, Skin, Fabric, Rubber

8 Improving classification accuracy RGB + NIR 6 bandpass filters


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