基于增强相关系数最大化算法的掌纹ROI裁剪

Noor Aldeen A. Khalid, Muhammad Imran Ahmad, Thulfiqar H. Mandeel, M. I. N. Isa, Raja Abdullah Raja Ahmad, Mustafa Zuhaer Nayef Al-Dabagh
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引用次数: 1

摘要

本文提出了一种提取掌纹生物特征图像感兴趣区域的新技术,同时消除了感兴趣区域提取过程中图像间的平移、旋转等畸变。一种被称为增强相关系数(ECC)的相似性度量在该方法中被用于更好的ROI提取和图像对齐,这有助于评估和确定失真。图像对齐方法的目标是找到使图像之间的不一致最小化的变形或变换。另一方面,为了验证所推荐方法的有效性,我们使用了PolyU掌纹数据集II来验证所推荐方法的有效性。实验结果表明,该方法的ROI提取精度高达99.8%,成功开发了鲁棒的ROI裁剪系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Palmprint ROI Cropping Based on Enhanced Correlation Coefficient Maximisation Algorithm
This paper proposes new technique to extract the Region of Interest (ROI) of palmprint biometric image while removing the distortion between images such as translation or rotation during ROI extraction. A similarity measure known as Enhanced Correlation Coefficient (ECC) is used in the proposed approach for better ROI extraction and image alignment, which helps to evaluate and determine the distortion. The objective of image alignment approaches are to find the deformation or transformation that minimizes the incongruities between images. After applying ECC algorithm the Region of Interest (ROI) is extracted from the palmprint by using moore neighbors algorithm, on the other hand, to verify and validate the efficacy of the recommended method the PolyU palmprint dataset II was used. The results show the high accuracy is 99.8% in deriving the ROI and developing a robust ROI cropping system successfully.
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