Two Dimensional Clipping Based Segmentation Algorithm for Grayscale Fingerprint Images
Author:
Affiliation:
1. Research Scholar, College of Computer and Information Science, Srinivas University, Mangaluru-575001, Karnataka, India
2. College of Computer and Information Science, Srinivas University, Mangaluru-575001, Karnataka, India
Abstract
Publisher
Srinivas University
Subject
General Medicine
Reference26 articles.
1. Zhang, J., Lai, R., & Kuo, C. C. J. (2012). Latent fingerprint detection and segmentation with a directional total variation model. In Proceedings - International Conference on Image Processing, ICIP, 1145–1148. DOI: https://doi.org/10.1109/ICIP.2012.6467067
2. Krishna Prasad, K. & Aithal, P. S. (2017). A Conceptual Study on Image Enhancement Techniques for Fingerprint Images. International Journal of Applied Engineering and Management Letters (IJAEML), 1(1), 63-72. DOI: http://dx.doi.org/10.5281/zenodo.831678
3. Krishna Prasad, K. & Aithal, P. S. (2017). Literature Review on Fingerprint Level 1 and Level 2 Features Enhancement to Improve Quality of Image. International Journal of Management, Technology, and Social Sciences (IJMTS), 2(2), 8-19. DOI: http://dx.doi.org/10.5281/zenodo.835608
4. Krishna Prasad, K. & Aithal, P. S. (2017). Fingerprint Image Segmentation: A Review of State of the Art Techniques. International Journal of Management, Technology, and Social Sciences (IJMTS), 2(2), 28-39. DOI: http://dx.doi.org/10.5281/zenodo.848191
5. Krishna Prasad, K. & Aithal, P. S. (2017). A Novel Method to Contrast Dominating Gray Levels during Image contrast Adjustment using Modified Histogram Equalization. International Journal of Applied Engineering and Management Letters (IJAEML), 1(2), 27-39. DOI: http://dx.doi.org/10.5281/zenodo.896653
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