Fingerprint Image Enhancement Using Adaptive Pre-processing of Data and K-means Segmentation
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

M.Tech / M.E / PhD Thesis | Electronics & Communication Engineering | India | Volume 4 Issue 6, June 2015

Fingerprint Image Enhancement Using Adaptive Pre-processing of Data and K-means Segmentation

Mohammed Shakeer.M.A, Nithin.M.V

An adaptive fingerprint image enhancement method is proposed in this paper. Which is the improvement of existing methods based on contextual filtering. Adaptive system implies the parameters of this method are automatically adjusted based on input fingerprint image. Method is comprised into five processing blocks where all the five blocks are updated with new and best technologies. Hence over all system is noval. Processing blocks are preprocessing, global analysis, local analysis, matched filtering and image segmentation. a non linear dynamic range adjustment method is performed in preprocessing and local analysis blocks. Different form of order statistical filtering are applied in global analysis and matched filtering. A new technique called K-means segmentation is used for image segmentation. These processing blocks yield an improved and new adaptive fingerprint image processing method. The performance of updated processing blocks is presented in evaluation part of this paper.

Keywords: Directional filtering, Fourier transform, image processing, spectral feature estimation, successive mean quantization transform

Edition: Volume 4 Issue 6, June 2015

Pages: 2807 - 2813

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How to Cite this Article?

Mohammed Shakeer.M.A, Nithin.M.V, "Fingerprint Image Enhancement Using Adaptive Pre-processing of Data and K-means Segmentation", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=SUB156016, Volume 4 Issue 6, June 2015, 2807 - 2813

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