APEX Institute of Technology Management B Tech Project

APEX Institute of Technology &Management B. Tech Project Presentation-2013 Fingerprint Recognition Project ID-1044 By Sandeep Kumar Panda Sailendra Sagar Patra Roll# ECE 200910024 Roll# ECE 200910023 Under the guidance of Mrs. T. Mita Kumari Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [1]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 Outline……. • • • Objective What is Fingerprint? What is Fingerprint Recognition? Algorithms For Fingerprint Recognition. Preprocessing Stages. Minutia Extraction. Minutia Match. Result And Discussion Conclusion Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [2]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 Objective Of Our Project • The objective is to implement Fingerprint Recognition Algorithm by Using Minutia Extraction and Minutia Matching. • The objective is to implement fingerprint recognition algorithm. The Region of Interest (ROI) for each fingerprint image is extracted after enhancing its quality. That is used to extract the minutia, followed by minutiae extraction. • • Application : • • • Data Security Crime Investigation Security Lock Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [3]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 What Is Fingerprint? • • Skin on human fingertips contains ridges and valleys which together forms distinctive patterns. These patterns are called FINGERPRINTS. However, shown by intensive research on fingerprint recognition, fingerprints are not distinguished by their ridges and furrows, but by features called Minutia, which are some abnormal points on the ridges. Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [4]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 • Among the variety of minutia types reported in literatures, two are mostly significant and in heavy usage: 1. Ridge ending- the ridge abrupt end of a 2. Ridge bifurcation- a single ridge that divides into two ridges Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [5]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 What Is Fingerprint Recognition? • Fingerprint recognition is the process of comparing questioned and known fingerprint against another fingerprint to determine if the impressions are from the same finger or palm. • It includes two sub-domains: one is fingerprint verification and the other is fingerprint identification. Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [6]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 Algorithms For Fingerprint Recognition Load Image Acquisition Histogram Equalization Enhancement Using FFT Preprocessing Stages Binarization Ridge Ending ROI Thinning Minutia Extraction Minutia Marking Align And Match Template Minutia Match Save Template Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [7]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 Pre Processing Stages…. • Histogram Equalization: 1. Histogram equalization is a technique of improving the global contrast of an image by adjusting the intensity distribution on a histogram. Original Histogram After Equalization Histogram Equalization Image Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [8]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 Pre Processing Stages…. • Enhancement by Fourier transform: The image enhancement by FFT is done by the following formula: Where, for x=0, 1, 2, ……. , 31 and y=0, 1, 2, ……. , 31. Enhanced FFT Image Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [9]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 Pre Processing Stages…. • Binarization: • Fingerprint Image Binarization is to transform the 8 -bit Gray fingerprint image to a 1 -bit image with 0 -value for ridges and 1 -value for furrows. • After the operation, ridges in the fingerprint are highlighted with black colour while furrows are white. A locally adaptive binarization method is performed to binarize the fingerprint image. • Such a named method comes from the mechanism of transforming a pixel value to 1 if the value is larger than the mean intensity value of the current block (16 x 16) to which the pixel belongs Binarized Image Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [10]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 Pre Processing Stages…. • Block Direction Estimation • The direction for each block of the fingerprint image with Wx. W in size(W is 16 pixels by default)is estimated. • The gradient values along x-direction (gx) and y-direction (gy) for each pixel of the block is calculated. • For each block, following formula is used to get the Least Square approximation of the block direction. Block Direction Image Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [11]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 Preprocessing Stages…… • ROI(Region Of Interest): • Two Morphological operations called ‘OPEN’ and ‘CLOSE’ are adopted. • The ‘OPEN’ operation can expand images and remove peaks introduced by background noise. • The ‘CLOSE’ operation can shrink images and eliminate small cavities. ROI Image Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [12]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 Minutia Extraction……. . • Ridge Thinning: • Ridge Thinning is to eliminate the redundant pixels of ridges till the ridges are just one pixel wide. • An iterative, parallel thinning algorithm is used for ridge thinning. Thinned Image Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [13]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 Minutia Extraction……. . • Minutia Marking: • After the fingerprint ridge thinning, marking minutia points is relatively easy. The concept of Crossing Number (CN) is widely used for extracting the Minutia. 0 1 0 0 0 1 0 1 0 0 1 Bifurcation Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 Termination Marked Image [14]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 Minutia Matching……. . • Minutia match algorithm determines whether the two minutiae sets are from same finger or not. • It include two stages: – Alignment Stage – Match Stage • Alignment stage: - Given two fingerprint images to be matched, any one minutia from each image is chosen, and the similarity of the two ridges associated with the two referenced minutia points is calculated • Match stage: After obtaining two set of transformed minutia points, the elastic match algorithm is used to count the matched minutia pairs by assuming two minutia having nearly the same position and direction are identical. Matched Image Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [15]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 RESULT AND DISCUSSION • Histogram Equalization Image: Original Image After Histogram Equalization Algorithm Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [16]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 RESULT AND DISCUSSION • Enhancement by Fourier transform: Image After Histogram Equalization Image After FFT Enhancement Algorithm Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [17]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 RESULT AND DISCUSSION • Binarization: Image After FFT Enhancement Binarized Image Algorithm Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [18]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 RESULT AND EXPERIMENT • Block Direction Estimation: • : Binarized Image Block Direction Estimation Algorithm Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [19]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 RESULT AND EXPERIMENT • ROI(Region Of Interest): Binarized Image Open Operation Close Operation ROI+Bound Algorithm Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [20]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 RESULT AND EXPERIMENT • Ridge Thinning: ROI Image Thinned Image Algorithm Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [21]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 RESULT AND EXPERIMENT • Minutia Marking: Thinned Image Minutia Marked Image Algorithm Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [22]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 RESULT AND DISCUSSION • Minutia Matching: • Here we had taken two different sets of fingerprints. 1. Two different angles of a same fingerprint 2. Fingerprints of two different finger. • Using Match Score we distinguish two fingerprints are same or not. Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [23]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 RESULT AND DISCUSSION • The match score value between the two images is 0. 67. • This value is greater or same as threshold value. • We conclude that these two fingerprints are of same person. Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [24]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 RESULT AND DISCUSSION • The match score value between the two images is 0. 37. • This value less than threshold value. • We conclude that these two fingerprints are of two different persons. Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [25]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 Conclusion • The above implementation was an effort to understand how Fingerprint Recognition is used as a form of biometric to recognize identities of human beings. • It includes all the stages from enhancement to minutiae extraction of fingerprints. • There are various standard techniques are used in the intermediate stages of processing. • At last minutiae extraction and comparison happens. Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [26]

APEX Institute of Technology &Management B. Tech Project Presentation-2013 Reference • Fingerprint database - FVC 2002 (Fingerprint Verification Competition 2002) • Rafael C. Gonzalez, Richard E Woods “Digital Image Processing” 2 nd edition, 2002. • K. Jain, F. Patrick, A. Arun , “Handbook of Biometrics”, Springer Science Business Media, LLC, 1 st edition, pp. 1 -42, 2008. • D. Maio, and D. Maltoni, “Direct gray-scale minutia detection in fingerprints”, IEEE Transactions Pattern Analysis and Machine Intelligence, vol. 19(1), pp. 27 -40, 1997. • D. Maltoni, D. Maio, and A. Jain, S. Prabhakar, “ 4. 3: Minutiae-based Methods’(extract) from Handbook of Fingerprint Recognition”, Springer, New York, pp. 141 -144, 2003. • E. Hastings, “A Survey of Thinning Methodologies”, Pattern analysis and Machine Intelligence, IEEE Transactions, vol. 4, Issue 9, pp. 869 -885, 1992. Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [27]

APEX Institute of Technology &Management THANK YOU Sandeep Kumar Panda Roll # ECE 200910024 Sailendra Sagar Patra Roll # ECE 200910023 [28]