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A real-time near infrared image acquisition system based on image quality assessment

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Abstract

This paper presents a real-time image acquisition system with an improved image quality assessment module to acquire high-quality near infrared (NIR) images. Thermal imaging plays a vital role in a wide range of medical and military applications. The demand for high-throughput image acquisition and image processing has continuously increased especially for critical medical and military purposes where executions under real-time constraints are required. This work implements an NIR image quality assessment module, which utilizes improved two-dimensional entropy and mask-based edge detection algorithms. The effectiveness of the proposed image quality assessment algorithms is demonstrated through the implementation of a complete finger-vein biometric system. The proposed model is implemented as an embedded system on a field programmable gate array prototyping platform. By including the image quality assessment module, the proposed system is able to achieve a recognition accuracy of 0.87 % equal error rate, and can handle real-time processing at 15 frames/s (live video rate). This is achieved through hardware acceleration of the proposed image quality assessment algorithms via a novel streaming architecture.

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Notes

  1. Finger placement in between illumination source and infrared camera for NIR image capture.

  2. In the context of image/video processing, real-time constraints refer to the requirement for the image processing tasks to be completed at live video rate which is typically 30 frames/s [2].

  3. Mathematical complexity for Fourier transform-based Canny edge detection on an \(M \times N\) image is O(MNlogMN).

  4. Mathematical complexity of a general convolution-based image processing operation on an \(M \times N\) image using \(m \times n\) kernel is O(MNmn).

  5. NIR images in a stream of video frames captured under different levels of infrared light intensity.

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Acknowledgments

This work is supported by the Ministry of Science, Technology and Innovation of Malaysia (MOSTI) and Universiti Teknologi Malaysia (UTM) under Technofund Grant Vote No. 3H001.

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Authors and Affiliations

  1. VeCAD Research Laboratory, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, UTM Skudai, 81310, Johor Bahru, Malaysia

    Y. H. Lee, M. Khalil-Hani, Rabia Bakhteri & Vishnu P. Nambiar

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  1. Y. H. Lee
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  2. M. Khalil-Hani
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  3. Rabia Bakhteri
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  4. Vishnu P. Nambiar
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Correspondence to Y. H. Lee.

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Lee, Y.H., Khalil-Hani, M., Bakhteri, R. et al. A real-time near infrared image acquisition system based on image quality assessment. J Real-Time Image Proc 13, 103–120 (2017). https://doi.org/10.1007/s11554-016-0586-y

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