**Author details**

related to image blur. **Figure 11** shows the main idea and framework of our system. In this chapter, we first studied the required image PPI for palmprint identification. Based on it, the minimum and maximum palm distances are determined in the FOV. It also provides a reference for image sensor resolution selection. Then, image blur is taken into consideration; different datasets are generated by Gaussian scale space function. The EER variation curves are obtained by different features on different databases. During the image collection process, when the palm moves out of the DOF, the sharpness of the captured image changes, so *eav* can be an index to

Based on the findings of this research, when designing new systems, the palm width in the captured image should be larger than 300 pixels; it at least should not smaller than 130 pixels. After the system is deployed, when the user is putting his/ her hand, the *eav* of the ROI image should be larger than 10. A more precise *eav* threshold should be obtained from the training dataset of the real system, because some other factors may affect the final EER distributions, such as the autoexposure-control and auto-white-balance-control functions of the imaging sensor. But the major trends are similar. The main contribution of this work is providing

This work is supported in part by the NSFC under grant 61332011, in part by the

Shenzhen Fundamental Research under grants JCYJ20180306172023949 and JCYJ20170412170438636, in part by the Shenzhen Institute of Artificial Intelligence

show whether the palm is put correctly in the DOF.

**Acknowledgements**

**Figure 11.**

*Biometric Systems*

*The framework of this chapter.*

and Robotics for Society.

**80**

some key references for system design based on image sharpness.

Xu Liang1,3†, Zhaoqun Li2,3†, Jinyang Yang<sup>1</sup> and David Zhang1,3,4\*

1 Harbin Institute of Technology, Shenzhen, China

2 The Chinese University of Hong Kong, Shenzhen, China

3 Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen, China

4 School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China

\*Address all correspondence to: davidzhang@cuhk.edu.cn; csdzhang@comp.polyu.edu.hk

† These authors are contributed equally.

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
