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Enhanced segmentation and complex-sclera features for human recognition with unconstrained visible-wavelength imaging

机译：增强的分割和复杂巩膜特征，可通过无限制的可见波长成像实现人识别

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Sclera recognition has received attention recently due to the distinctive features extracted from blood vessels within the sclera. However, uncontrolled human pose, multiple iris gaze directions, different eye image capturing distance and variation in lighting conditions lead to many challenges in sclera recognition. Therefore, we propose an enhanced system for sclera recognition with visible-wavelength eye images captured in unconstrained conditions. The proposed segmentation algorithm fuses multiple color space skin classifiers to overcome the noise factors introduced through acquiring sclera images such as motion, blur, gaze and rotation. We also propose a blood vessel enhancement and feature extraction method which we denote as complex-sclera features to increase the adaptability to noisy blood vessel deformations. The proposed system is evaluated using UBIRIS.v1, UBIRIS.v2 and UTIRIS databases and the results are promising in terms of accuracy and suitability in real-time applications due to low processing times.

机译：由于从巩膜内血管中提取的独特特征，巩膜识别最近受到关注。然而，不受控制的人的姿势，多个虹膜注视方向，不同的眼睛图像捕获距离以及光照条件的变化导致巩膜识别方面的许多挑战。因此，我们提出了一种用于巩膜识别的增强系统，该系统具有在不受约束的条件下捕获的可见波长眼睛图像。提出的分割算法融合了多个颜色空间皮肤分类器，以克服通过获取巩膜图像（例如运动，模糊，凝视和旋转）而引入的噪声因素。我们还提出了一种血管增强和特征提取方法，我们将其表示为复杂巩膜特征，以增加对嘈杂的血管变形的适应性。使用UBIRIS.v1，UBIRIS.v2和UTIRIS数据库对所提出的系统进行了评估，由于处理时间短，因此在实时应用中的准确性和适用性方面，结果令人鼓舞。

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来源
《2016 International Conference on Biometrics》|2016年|1-8|共8页
会议地点 Halmstad(SE)
作者
S. Alkassar; W. L. Woo; S. S. Dlay; J. A. Chambers;
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作者单位

School of Electrical and Electronic Engineering, Newcastle University, Newcastle upon Tyne, UK;

School of Electrical and Electronic Engineering, Newcastle University, Newcastle upon Tyne, UK;

School of Electrical and Electronic Engineering, Newcastle University, Newcastle upon Tyne, UK;

School of Electrical and Electronic Engineering, Newcastle University, Newcastle upon Tyne, UK;

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原文格式 PDF
正文语种 eng
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关键词
Image segmentation; Biomedical imaging; Skin; Blood vessels; Image color analysis; Feature extraction; Discrete wavelet transforms;

机译：图像分割;生物医学成像;皮肤;血管;图像颜色分析;特征提取;离散小波变换;

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1. Enhanced Gender Recognition System Using an Improved Histogram of Oriented Gradient (HOG) Feature from Quality Assessment of Visible Light and Thermal Images of the Human Body [J] . Dat Tien Nguyen, Kang Ryoung Park Sensors . 2016,第7期

机译：改进的性别识别系统，使用改进的定向梯度直方图（HOG）特征进行人体可见光和热图像的质量评估
2. Unconstrained Facial Expression Recognition Based on Feature Enhanced CNN and Cross-Layer LSTM [J] . Ying TONG, Rui CHEN, Ruiyu LIANG IEICE transactions on information and systems . 2020,第11期

机译：基于特征增强的CNN和跨层LSTM的无约束面部表情识别
3. Editorial: Towards feature extraction in unconstrained image recognition environments [J] . A.P. James International Journal of Applied Pattern Recognition . 2015,第4期

机译：社论：在不受限制的图像识别环境中实现特征提取
4. Enhanced segmentation and complex-sclera features for human recognition with unconstrained visible-wavelength imaging [C] . S. Alkassar, W. L. Woo, S. S. Dlay, IAPR International Conference on Biometrics . 2016

机译：增强的分割和复杂巩膜特征，具有无约束可见波长成像的人为识别
5. The design and use of unconstrained image filters and features for SAR detection and recognition. [D] . Shenoy, Rajesh Krishna. 2001

机译：无约束图像滤波器的设计和使用以及用于SAR检测和识别的功能。
6. Enhanced Gender Recognition System Using an Improved Histogram of Oriented Gradient (HOG) Feature from Quality Assessment of Visible Light and Thermal Images of the Human Body [O] . Dat Tien Nguyen, Kang Ryoung Park 2016

机译：使用改进的方向梯度直方图（HOG）特征的增强型性别识别系统来自人体可见光和热图像的质量评估
7. Iris Recognition: Measuring Feature’s Quality for the Feature Selection in Unconstrained Image Capture Environments [O] . Hugo Proença, Luís A. Alex, When L. Flom, 2009

机译：虹膜识别：在不受约束的图像捕获环境中，通过测量特征质量来选择特征

Enhanced segmentation and complex-sclera features for human recognition with unconstrained visible-wavelength imaging

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