优质、正常和劣质指纹图像的不均匀背景提取与分割

S. Jambhorkar, S. Gornale, V. Humbe, R. Manza, K V Kale
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引用次数: 4

摘要

本文提出了一种基于形态学变换的指纹图像提取和分割算法,研究了优质、正常和劣质指纹图像的背景不均匀问题。实验结果表明,该算法能较好地提取出质量好的、正常的和质量差的指纹图像的背景,并能很好地分割出前景区域。该算法在FVC2002数据库上进行了测试和执行,并通过主观和客观质量指标对算法的性能进行了评价。该算法能够在不影响指纹图像结构的情况下去除多余信息,并将生成图像的存储空间减少了77%。研究结果将为指纹自动识别系统的精确特征提取提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Uneven Background Extraction And Segmentation Of Good, Normal And Bad Quality Fingerprint Images
In this paper, we have considered a problem of uneven background extraction and segmentation of good, normal and bad quality fingerprint images, though we propose an algorithm based on morphological transformations. Our result shows that the proposed algorithm can successfully extract the background of good, normal and bad quality images of fingerprint and well segment the foreground area. The algorithm has been tested and executed on FVC2002 database and the performance of proposed algorithm is evaluated through subjective and objective quality measures. This algorithm gives good and promising result and found suitable to remove superfluous information without affecting the structure of fingerprint image as well as reduces the storage space for the resultant image upto 77%. Our results will be useful for precise feature extraction in automatic fingerprint recognition system.
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