Title: Towards contactless palm region extraction in complex environment

Authors: Tingting Chai; Shenghui Wang; Dongmei Sun

Addresses: Institute of Information Science, Beijing Jiaotong University, No. 3 Shangyuancun, Haidian District, Beijing 100044, China ' Institute of Information Science, Beijing Jiaotong University, No. 3 Shangyuancun, Haidian District, Beijing 100044, China ' Institute of Information Science, Beijing Jiaotong University, No. 3 Shangyuancun, Haidian District, Beijing 100044, China

Abstract: Palm region of interest (ROI) extraction is an indispensable procedure in palmprint recognition. Prior works generally perform well on palm ROI extraction because of dedicated devices and well-controlled environment. To make hand placement less-constrained and improve usability, mobile palmprint recognition has attracted a wide attention in recent years. For mobile phone images captured in complex natural environment, palm ROI extraction is a challenging work due to varying illumination, complex background and contactless acquisition mode. In this paper, a mobile palmprint dataset (SPIC) is at first established with five smartphones, comprising 4000 images collected from 128 persons in two separate sessions. Furthermore, a novel pre-processing approach is proposed to achieve ROI extraction in mobile scenarios, which include colour component selection, learning-based fast hand segmentation and geometry-driven valley point location. Experimental results demonstrate that the proposed method can achieve high extraction accuracy and computational efficiency on PolyU1.0, HA-BJTU and SPIC palmprint databases.

Keywords: palm ROI extraction; palmprint recognition; hand segmentation; contour tracking; valley point detection.

DOI: 10.1504/IJBM.2018.093635

International Journal of Biometrics, 2018 Vol.10 No.3, pp.232 - 254

Received: 01 Dec 2017
Accepted: 15 Apr 2018
Published online: 30 Jul 2018 *

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