De-noising Slap Fingerprint Images for Accurate Slap Fingerprint Segmentation
De-noising Slap Fingerprint Images for Accurate Slap Fingerprint Segmentation
复制标题
拍打指纹图像去噪，实现准确的拍打指纹分割
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
C. K. Mohan
中科院分区：
文献类型：
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作者：
N. P. Ramaiah;C. K. Mohan
指纹具有独特的特性，如独特性和持久性。有时，使用SLAP指纹扫描仪采集指纹图像时，可能会有一些噪声数据。这种噪声会导致不正确的拍击指纹分割，从而降低指纹匹配的性能。消除重复的过程被称为重复数据删除，这需要清晰的质量指纹。在进行掌纹分割时，由于数据中存在噪声，导致部分指纹图像分割不正确。本文尝试通过对指纹图像进行二值化，并利用8邻域对期望区域进行区域标记来去除指纹数据中存在的噪声，以实现准确的指纹分割。实验结果表明，指纹分割率从78%提高到99%。
Fingerprints have unique properties like distinctiveness and persistence. Sometimes, fingerprint images can have some noisy data while capturing them using slap fingerprint scanners. This noise causes improper slap fingerprint segmentation due to which the performance of fingerprint matching decreases. The process of eliminating duplicates is called de-duplication which requires the plain quality fingerprints. While doing the segmentation of slap fingerprints, some of the fingerprint images are improperly segmented because of the noise present in the data. In this paper, an attempt is made to remove the noise present in the slap fingerprint data using binarization of slap fingerprint image, and region labeling of desired regions with 8-adjacency neighborhood for accurate slap fingerprint segmentation. Experimental results demonstrate that the fingerprint segmentation rate is improved from 78% to 99%.