ISSN 2394-5125
 

Research Article 


IMAGE FUSION BASED MULTIMODAL BIOMETRIC RECOGONITION

Dr.A.Lakshmi, S.Jeevitha, N.Thenmoezhi, N.Bhuvaneswary.

Abstract
Multi focus image fusion in multimodal imaging for analysis is a process of fusing two or more images (i.e. iris & face scan images) to obtain a new one which contains a more accurate description of the individual source images. It is used to reduce the problems like blocking, ringing artifacts occurs because of DCT. The low frequency sub-band coefficients are fused by selecting coefficient having maximum spatial frequency. It indicates the overall active level of an image. The high frequency sub-band coefficients are fused by selecting coefficients having maximum code Finally, fused two different frequency sub-bands are inverse transformed to reconstruct fused image. after that Automatic defects detection in Multimodal images is very important in many diagnostic and therapeutic applications. Because of high quantity data in multimodal images and blurred boundaries, and classification is very hard. This work has introduced one automatic detection method to increase the accuracy and yield anddecrease the diagnosis time. The goal is classifying the tissues to two classes of authorized and unauthorized using feed forward neural network.

Key words: DCT, multimodal imaging, image fusion


 
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How to Cite this Article
Pubmed Style

Dr.A.Lakshmi, S.Jeevitha, N.Thenmoezhi, N.Bhuvaneswary. IMAGE FUSION BASED MULTIMODAL BIOMETRIC RECOGONITION. JCR. 2020; 7(4): 1445-1453. doi:10.31838/jcr.07.04.247


Web Style

Dr.A.Lakshmi, S.Jeevitha, N.Thenmoezhi, N.Bhuvaneswary. IMAGE FUSION BASED MULTIMODAL BIOMETRIC RECOGONITION. http://www.jcreview.com/?mno=99497 [Access: May 30, 2021]. doi:10.31838/jcr.07.04.247


AMA (American Medical Association) Style

Dr.A.Lakshmi, S.Jeevitha, N.Thenmoezhi, N.Bhuvaneswary. IMAGE FUSION BASED MULTIMODAL BIOMETRIC RECOGONITION. JCR. 2020; 7(4): 1445-1453. doi:10.31838/jcr.07.04.247



Vancouver/ICMJE Style

Dr.A.Lakshmi, S.Jeevitha, N.Thenmoezhi, N.Bhuvaneswary. IMAGE FUSION BASED MULTIMODAL BIOMETRIC RECOGONITION. JCR. (2020), [cited May 30, 2021]; 7(4): 1445-1453. doi:10.31838/jcr.07.04.247



Harvard Style

Dr.A.Lakshmi, S.Jeevitha, N.Thenmoezhi, N.Bhuvaneswary (2020) IMAGE FUSION BASED MULTIMODAL BIOMETRIC RECOGONITION. JCR, 7 (4), 1445-1453. doi:10.31838/jcr.07.04.247



Turabian Style

Dr.A.Lakshmi, S.Jeevitha, N.Thenmoezhi, N.Bhuvaneswary. 2020. IMAGE FUSION BASED MULTIMODAL BIOMETRIC RECOGONITION. Journal of Critical Reviews, 7 (4), 1445-1453. doi:10.31838/jcr.07.04.247



Chicago Style

Dr.A.Lakshmi, S.Jeevitha, N.Thenmoezhi, N.Bhuvaneswary. "IMAGE FUSION BASED MULTIMODAL BIOMETRIC RECOGONITION." Journal of Critical Reviews 7 (2020), 1445-1453. doi:10.31838/jcr.07.04.247



MLA (The Modern Language Association) Style

Dr.A.Lakshmi, S.Jeevitha, N.Thenmoezhi, N.Bhuvaneswary. "IMAGE FUSION BASED MULTIMODAL BIOMETRIC RECOGONITION." Journal of Critical Reviews 7.4 (2020), 1445-1453. Print. doi:10.31838/jcr.07.04.247



APA (American Psychological Association) Style

Dr.A.Lakshmi, S.Jeevitha, N.Thenmoezhi, N.Bhuvaneswary (2020) IMAGE FUSION BASED MULTIMODAL BIOMETRIC RECOGONITION. Journal of Critical Reviews, 7 (4), 1445-1453. doi:10.31838/jcr.07.04.247