Iris Image Blur Detection with Multiple Kernel Learning

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概要

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• In this letter, we analyze the influence of motion and out-of-focus blur on both frequency spectrum and cepstrum of an iris image. Based on their characteristics, we define two new discriminative blur features represented by Energy Spectral Density Distribution (ESDD) and Singular Cepstrum Histogram (SCH). To merge the two features for blur detection, a merging kernel which is a linear combination of two kernels is proposed when employing Support Vector Machine. Extensive experiments demonstrate the validity of our method by showing the improved blur detection performance on both synthetic and real datasets.

著者

• Mao Ling

  School Of Electronic Engineering University Of Electronic Science And Technology Of China

• Xie Mei

  School Of Electronic Engineering University Of Electronic Science And Technology Of China

• PAN Lili

  School of Electronic Engineering, University of Electronic Science and Technology of China

関連論文

• Digital Image Stabilization Based on Correction for Basic Reference Frame Jitter
• Iris Image Blur Detection with Multiple Kernel Learning
• Iris Image Blur Detection with Multiple Kernel Learning

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