%0 Journal Article %1 Kumar_2015 %A Kumar, S.Siva %A Alikhan, J.Sulthan %D 2015 %I Auricle Technologies, Pvt., Ltd. %J International Journal on Recent and Innovation Trends in Computing and Communication %K Dictionary Field Latent Orientation Transform fingerprint %N 3 %P 1087--1089 %R 10.17762/ijritcc2321-8169.150342 %T Enhancement of Latent Fingerprint Recognition Using Global Transform %U http://dx.doi.org/10.17762/ijritcc2321-8169.150342 %V 3 %X Latent Fingerprints plays a vital role in identifying thefts, crime etc. Latent fingerprints are of 3 types. Noise in the Latent Fingerprints is removed by smoothing. Manual marking in Latent Fingerprint is slow and also latent examiner may make mistake while marking. The minutiae in the same latent marked by different latent examiners or even by the same examiner (but at different times) may not be the same. To overcome this issue new Orientation field estimation algorithm is introduced. It based on latent fingerprint feature extraction and edge detection. Orientation field estimation algorithm has dictionary construction stage. Dictionary Construction has 2 Stages. i) Offline stage ii) online stage. Orientation field estimation algorithm is applied for Overlapped fingerprint. Hough transform is used for detecting edges. It is shown that this method is slower to recognize latent fingerprint feature extraction and edge linking. In order to further increase the speed and perfect edge linking Hough transform method can be modified for better performance. Global transform is used for perfect edge linking and get the full fingerprint structure and comparison is made between two transforms to show which transform is better.

@article{Kumar_2015, abstract = {Latent Fingerprints plays a vital role in identifying thefts, crime etc. Latent fingerprints are of 3 types. Noise in the Latent Fingerprints is removed by smoothing. Manual marking in Latent Fingerprint is slow and also latent examiner may make mistake while marking. The minutiae in the same latent marked by different latent examiners or even by the same examiner (but at different times) may not be the same. To overcome this issue new Orientation field estimation algorithm is introduced. It based on latent fingerprint feature extraction and edge detection. Orientation field estimation algorithm has dictionary construction stage. Dictionary Construction has 2 Stages. i) Offline stage ii) online stage. Orientation field estimation algorithm is applied for Overlapped fingerprint. Hough transform is used for detecting edges. It is shown that this method is slower to recognize latent fingerprint feature extraction and edge linking. In order to further increase the speed and perfect edge linking Hough transform method can be modified for better performance. Global transform is used for perfect edge linking and get the full fingerprint structure and comparison is made between two transforms to show which transform is better.}, added-at = {2015-08-06T08:58:03.000+0200}, author = {Kumar, S.Siva and Alikhan, J.Sulthan}, biburl = {https://www.bibsonomy.org/bibtex/2c9c899d39a10c9ff884a0d75eb4cebfc/ijritcc}, doi = {10.17762/ijritcc2321-8169.150342}, interhash = {abff63a6c9ec15e3f8d20114b5ee0bd6}, intrahash = {c9c899d39a10c9ff884a0d75eb4cebfc}, journal = {International Journal on Recent and Innovation Trends in Computing and Communication}, keywords = {Dictionary Field Latent Orientation Transform fingerprint}, month = {march}, number = 3, pages = {1087--1089}, publisher = {Auricle Technologies, Pvt., Ltd.}, timestamp = {2015-08-06T08:58:03.000+0200}, title = {Enhancement of Latent Fingerprint Recognition Using Global Transform}, url = {http://dx.doi.org/10.17762/ijritcc2321-8169.150342}, volume = 3, year = 2015 }