Abstract
The scale of deployment of biometric identity-verification systems has recently seen an enormous increase owing to the need for more secure and reliable way of identifying people. Footprint identification which can be defined as the measurement of footprint features for recognizing the identity of a user has surfaced recently. This study is based on a biometric personal identification method using static footprint features viz. friction ridge / texture and foot shape / silhouette. To begin with, naked footprints of users are captured; images then undergo pre processing followed by the extraction of two features; shape using Gradient Vector Flow （ GVF ） snake model and minutiae extraction respectively. Matching is then effected based on these two features followed by a fusion of these two results for either a reject or accept decision. Our shape matching feature is based on cosine similarity while the texture one is based on miniature score matching. The results from our research establish that the naked footprint is a credible biometric feature as two barefoot impressions of an individual match perfectly while that of two different persons shows a great deal of dissimilarity. Normal 0 false false false IN X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Doi : 10.12777/ijse.5.2.29-35 How to cite this article: King , R.R. and Xiaopeng , W . (2013). S tudy of Biometric I dentification Method Based on Naked Footprint . International Journal of Science and Engineering , 5(2),18-24. Doi: 10.12777/ijse.5.2.29-35 ] Normal 0 false false false IN X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}
Highlights
The persistent insecurity in our world today has necessitated the continuous search for new forms of security which are more reliable and less vulnerable against intruders’ attacks
Static footprint based on Euclidean distance[7], Modified Sequential Haar Energy Transform (MSHET) [1], Center of pressure (COP) Using Principle Component Analysis (PCA) [2], Four orientation feature based approaches namely “Ordinal Code” (OC), “Binary Orientation Co-occurrence Vector” (BOCV), “Competitive Code” (CC), and “Robust Line Orientation Code” (RLOC) [12], Hidden Markov Models (HMM) [5] are exploited for recognition
The Receiver Operating Characteristic curve (ROC) curve is a visual rendition of the trade-off between the False Acceptance Rate (FAR) and the False reject Rate (FRR), in other words, the curve plots the true positives against the false positives
Summary
The persistent insecurity in our world today has necessitated the continuous search for new forms of security which are more reliable and less vulnerable against intruders’ attacks. Direct attacks are carried out by falsifying the biometric trait of a user and presenting this falsified information to the biometric system to gain access One such example [11] is to fool a fingerprint system by copying the fingerprint of another person and creating an artificial or gummy finger which can be presented to the biometric system to falsely gain access. Personal identification using footprint can be carried out by using any one of the two important features of the foot; namely static and dynamic. Static feature requires stand-up posture at fixed positions every time from the subject, whereas the dynamic feature deals with the walking behaviour of a person. This proposed system is based on the former. Static footprint based on Euclidean distance[7], Modified Sequential Haar Energy Transform (MSHET) [1], Center of pressure (COP) Using Principle Component Analysis (PCA) [2], Four orientation feature based approaches namely “Ordinal Code” (OC), “Binary Orientation Co-occurrence Vector” (BOCV), “Competitive Code” (CC), and “Robust Line Orientation Code” (RLOC) [12], Hidden Markov Models (HMM) [5] are exploited for recognition
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