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Point and local neighborhood operations fusion for efficient fingerprint enhancement

机译:点和本地邻域操作融合可有效增强指纹

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摘要

Fingerprint is an important evidence in criminal investigation process. It is considered as the most reliable biometric measure in forensic sciences. Many studies have been proposed in the subject of fingerprint image enhancement but most of them either worked on point based operations or local neighborhood operations. This paper presents an efficient fingerprint enhancement approach by combining the point and local operations. Point based adaptive histogram equalization method along with local neighborhood based median filter method improves the overall quality of fingerprint by removing noise from image and preserves its information content in better way than individual point or local operations. The image entropy is used as an objective assessment method for the analysis of quality of fingerprint image.
机译:指纹是刑事侦查过程中的重要证据。在法医学中,它被认为是最可靠的生物测定方法。已经提出了许多关于指纹图像增强的研究,但是它们中的大多数都基于点的操作或局部邻域操作。本文提出了一种结合点和局部操作的有效指纹增强方法。基于点的自适应直方图均衡方法与基于局部邻域的中值滤波方法相结合,可通过去除图像中的噪声来改善指纹的整体质量,并以比单个点或局部操作更好的方式保留其信息内容。图像熵被用作分析指纹图像质量的客观评估方法。

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