Enhanced Fingerprint Recognition by Reference Auto-correction with FCM-CBIR strategy

P. Thejaswini, R. Srikantaswamy, A. Manjunatha
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Abstract

Nowadays fingerprint recognition becomes an important biometric trait for authenticating and identifying individuals. Various researchers found that there is a change in the fingerprint images due to the variation in temperature. Hence in this paper, an effective fingerprint recognition system is developed to recognize the fingerprint images varied due to environmental changes like temperature. Hence, we propose FCM-CBIR technique for the identification of fingerprint during change of temperature. In this, clustering is performed using fuzzy $\mathbf{c}$ means clustering algorithm and the image retrieval process is performed using CBIR Content Based Image Retrieval. By using this proposed method, the unrecognized fingerprint due to temperature changes has been identified. The performances are measured using the various fingerprint images collected from real time environment.
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基于FCM-CBIR的参考自动校正增强指纹识别
目前,指纹识别已成为一种重要的生物特征识别手段。不同的研究人员发现,由于温度的变化,指纹图像会发生变化。因此,本文开发了一种有效的指纹识别系统,用于识别温度等环境变化下的指纹图像。因此,我们提出了FCM-CBIR技术用于温度变化下的指纹识别。其中,聚类使用模糊$\mathbf{c}$ means聚类算法,图像检索过程使用CBIR基于内容的图像检索。利用该方法可以识别出温度变化引起的指纹识别问题。使用从实时环境中采集的各种指纹图像来测量性能。
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