Latent Fingerprint Indexing and Segmentation Techniques
Harivans Pratap Singh1, Priti Dhimri2, Shailesh Tiwari3

1Harivans Pratap Singh, Research Scholar, Assistant Professor, Department of Computer Science & Engineering, ABES Engineering College, Ghaziabad (Uttar Pradesh) India.
2Priti Dimri, Department of Computer Science and Applications, G.B. Pant Engineering College, Ghurdauri (Uttarakhand), India.
3Shailesh Tiwari, Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad (Uttar Pradesh) India.
Manuscript received on 07 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript published on 30 April 2019 | PP: 1234-1238 | Volume-8 Issue-6, April 2019 | Retrieval Number: F3805048619/19©BEIESP
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Abstract: Over the past few years, fingerprints have been considered the most sensitive and crucial identification basis for low enforcement agencies. In crime scene and forensics, recording of latent fingerprints from uneven and noisy surface is difficult task and conventional algorithm fails in most of the time. A robust orientation field estimation algorithm is the need of the time to recognize the poor quality latent. To overcome the limitations of conventional algorithm various techniques have been proposed in the last one decade. In this paper a comparative study has been done of state -of -the- art techniques with their advancements and limitations. A thorough orientation to the basics of fingerprint indexing, its classification and feature extraction has been discussed .Our proposal aims at effectively minimizing the difficulties faced to separate ridges and segmentation of latent images reducing search time and computational complexity and to identify the correct pattern from latent or partial fingerprints while optimizing the system retrieval performance.
Keyword: Coherence, Indexing, Latent, Minutiae, Ridges, Skeleton, Variation.
Scope of the Article: Artificial Intelligent Methods, Models, Techniques