【24h】

Finger Shape Extraction and Expansion by Wavelet Transform and Hand Shape Analysis and Recognition

机译:小波变换的手指形状提取与扩展以及手形分析与识别

获取原文
获取原文并翻译 | 示例

摘要

This research uses the object extracting technique to extract the - thumb, index, middle, ring, and small fingers from the hand images. The algorithm developed in this research can find the precise locations of the fingertips and the finger-to-finger-valleys. The extracted fingers contain many useful geometry features. One can use these features to do the person identification. The geometry descriptor is used to transfer geometry features of these finger images to another featuredomain for image-comparison. Image is scaled and the reverse Wavelet Transform is performed to the finger image to make the finger image has more salient feature. Image subtraction is used to exam the difference of the two images. This research uses the finger-image and the palm image as the features to recognize different people. In this research, totally eighteen hundred and ninety comparisons are conducted. Within these eighteen hundred and ninety comparisons, two hundred and seventy comparisons are conducted for self-comparison. The other sixteen hundred and twenty comparisons are conducted for comparisons between two different persons' finger images. The false accept rate is 0%, the false reject rate is 1.9%, and the total error rate is 1.9%.
机译:本研究使用对象提取技术从手图像中提取拇指,食指,中指,无名指和小指。在这项研究中开发的算法可以找到指尖和手指到手指谷的精确位置。提取的手指包含许多有用的几何特征。可以使用这些功能来进行人员识别。几何描述符用于将这些手指图像的几何特征转移到另一个特征域以进行图像比较。缩放图像并对手指图像执行反向小波变换,以使手指图像具有更多显着特征。图像减法用于检查两个图像的差异。这项研究以手指图像和手掌图像为特征来识别不同的人。在这项研究中,总共进行了189次比较。在这189项比较中,进行了270项比较以进行自我比较。进行另外的一百二十次比较,以比较两个不同人的手指图像。错误接受率为0%,错误拒绝率为1.9%,总错误率为1.9%。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号