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Zero-crossing rates of wavelet frame representations for texture classification

Zero-crossing rates of wavelet frame representations for texture classification

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The zero-crossing rates (ZCRs) of the wavelet frame representation of texture images are proposed as features for texture classification. Results indicate that ZCR features lower the probability of error (PE) by 40% over energy (EN) and correlation coefficient features. Augmenting ZCR features with EN features improves the PE by 70% over ZCR features alone.

Inspec keywords: image representation; wavelet transforms; image classification; image texture

Other keywords: ZCR features; probability of error; energy features; texture classification; image processing; zero-crossing rates; wavelet frame representation; texture images; correlation coefficient features

Subjects: Optical, image and video signal processing; Image recognition; Integral transforms in numerical analysis; Computer vision and image processing techniques; Integral transforms in numerical analysis

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