Angular Bisector Fitting of Finger Valley Edge for Palmprint Localization

CHEN Qi; ZHANG Qing; CHEN Hao; LENG Lu; LI Ming

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Angular Bisector Fitting of Finger Valley Edge for Palmprint Localization

更新时间：2026-09-04

- Angular Bisector Fitting of Finger Valley Edge for Palmprint Localization
- Vol. 35, Issue 2, Pages: 56-60(2018)
- 作者机构：
  
  1. 南昌航空大学机构信息工程学院,江西,南昌,330063
  2. 南昌航空大学软件学院,江西,南昌,330063
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2018
- 稿件说明：
移动端阅览
陈琪, 张情, 陈昊, 冷璐, 黎明. 基于指根边缘夹角平分线拟合的掌纹定位方法[J]. 微电子学与计算机, 2018, 35(2): 56-60.

CHEN Qi, ZHANG Qing, CHEN Hao, et al. Angular Bisector Fitting of Finger Valley Edge for Palmprint Localization[J]. 2018, 35(2): 56-60.
陈琪, 张情, 陈昊, 冷璐, 黎明. 基于指根边缘夹角平分线拟合的掌纹定位方法[J]. 微电子学与计算机, 2018, 35(2): 56-60. DOI：

CHEN Qi, ZHANG Qing, CHEN Hao, et al. Angular Bisector Fitting of Finger Valley Edge for Palmprint Localization[J]. 2018, 35(2): 56-60. DOI：

摘要

针对移动终端复杂背景引起的感兴趣区域(Region of interest

ROI)定位不准确性

提出一种基于指间边缘夹角角平分线的掌纹ROI定位方法.首先在YCbCr颜色空间提取边缘

即追踪掌纹轮廓

然后用椭圆模型去除伪边缘和噪声

通过形态学操作对实际边缘进行平滑和修补

从而将指根边缘区域化.在所得两个边缘区域上

用最小二乘法拟合边缘夹角平分线来定位指窝点.该方法能有效去除指根附近背景的干扰

克服手掌轻微旋转引起的ROI定位偏差

实验表明该方法在移动设备环境下能够达到较高的正确率和认证精度.

Abstract

Aiming at the inaccurate positioning of region of interest (ROI)

a method of ROI localization based on angular bisector of finger valley edge is proposed. Firstly

the edges are extracted in the YCbCr color space

i.e. tracing the palmprint contour. Then the pseudo edges and noises are removed with the ellipse model. In addition

the actual edges are smoothed and repaired with morphological manipulation

which leads to the regionalization of valley edges between fingers. On the two obtained edge regions

the two angular bisector are fitted with least square method to detect two key-points of finger valley. The proposed method cannot only remove the disturbance in the background near the finger valley

but also overcome the deviation of ROI localization resulted from the slight rotation of the palm. The experimental results confirm that the proposed method can achieve high accuracy and verification precision in mobile device environment.

关键词

Keywords

references

Z Guo, D Zhang, L Zhang, et al. Palmprint verification using binary orientation co-occurrence vector[J]. Pattern Recognition Letters, 2009, 30(13): 1219-1227. DOI: 1219

黄申, 徐成, 屈景辉, 等. 基于小波理论对掌纹主线提取和修复[J]. 中国图象图形学报, 2006, 11(8): 1139-1149. DOI: 1139

M Aykut, M Ekinci. Developing a contactless palmprint authentication system by introducing a novel ROI extraction method[J]. Image % Vision Computing, 2015, 40(C): 65-74. DOI: 65

D Zhang, W K Kong, J You, et al. Online palmprint identification[J]. IEEE Transactions on Pattern Analysis % Machine Intelligence, 2003, 25(9): 1041-1050. DOI: 1041

L Leng, G Liu, M Li, et al. Logical conjunction of triple-perpendicular-directional translation residual for contactless palmprint preprocessing[C]//11th International Conference on Information Technology: New Generations, Washington, DC, USA, 2014: 523-528.

M M El-Seddek, M S Morsy, F W Zaki. A radon transform based technique for identification of palmprint images[C]//IEEE on Radio Science Conference. Florida, USA. 2015: 189-195.

赵杰, 桑庆兵, 刘毅锟. 基于分裂式K均值聚类的肤色检测方法[J]. 计算机工程与应用, 2014, 50(1): 134-138. DOI: 134

J S Kim, Gen Li, B G Son, et al. An empirical study of palmprint recognition for mobile phones[J]. International Workshop on Advanced Image Technology, 2015, 61 (3) : 311-319. DOI: 311

G Li, J Kim. Palmprint recognition with local micro-structure tetra pattern[J]. Pattern Recognition, 2017(61): 29-46. DOI: 29

G K O Michael, T Connie, A B J Teoh. Touch-less palm print biometrics: Novel design and implementation[J]. Image % Vision Computing, 2008, 26(12): 1551-1560. DOI: 1551

李艳, 吴贵芳, 戴高乐, 等. 一种新的掌纹轮廓特征点提取算法[J]. 微电子学与计算机, 2010, 27(5): 90-94. DOI: 90

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