Munaga V. N. K. Prasad

Fingerprint template protection using multiline neighboring relation

Abstract Security and privacy concern of biometric information leads to the attention for generating cancellable template from the original biometric template. We proposed an alignment free cancellable template generation by construction of M rectangles with different orientations around every reference minutiae followed by the calculation of rotation invariant and translation invariant neighboring relation, plane based quantization for bit string generation and matching. The proposed method fulfills non-invertibility, accuracy, diversity and revocability properties which are the primary requirements of cancellable template design. The EER obtained for FVC 2002 DB1, DB2, and DB3 is 0.62%, 1.33%, and 2.64% for same key scenario. The proposed method shows the better performance for FVC 2002 DB1, DB2, and DB3 compared to the existing methods (Wang & Hu, 2012, 2014; Ahmad et al., 2011).

k-Nearest Neighborhood Structure (k-NNS) based alignment-free method for fingerprint template protection

In this paper we focus on constructing k-Nearest Neighborhood Structure(k - NNS) for minutiae points in a fingerprint image. For each minutiae point in a fingerprint, a k - NNS is constructed taking the local and global features of minutiae points. This structure is quantized and mapped onto a 2D array to generate a fixed length 1D bit-string. Further this bit string is applied with a DFT to generate a complex vector. Finally the complex vector is multiplied by a user specific random matrix to generate the cancelable template. We tested our proposed method on database FV C2002 and experimental results depicts the validity of the proposed method in terms of requirements of cancelable biometrics namely diversity, accuracy, irreversibility and revocability.

Generating cancellable fingerprint templates based on Delaunay triangle feature set construction

In this study, the authors propose a novel fingerprint template protection scheme that is developed using Delaunay triangulation net constructed from the fingerprint minutiae. The authors propose two methods namely FS_INCIR and FS_AVGLO to construct a feature set from the Delaunay triangles. The feature set computed is quantised and mapped to a 3D array to produce fixed length 1D bit string. This bit string is applied with a DFT to generate a complex vector. Finally, the complex vector is multiplied by users key to generate a cancellable template. The proposed computation of feature set maintained a good balance between security and performance. These methods are tested on FVC 2002 and FVC 2004 databases and the experimental results show satisfactory performance. Further, the authors analysed the four requirements namely diversity, revocability, irreversibility and accuracy for protecting biometric templates. Thus, the feasibility of proposed scheme is depicted.

A Novel Iris Recognition System

Iris recognition as an emerging biometric recognition approach and itpsilas becoming a very active topic in both research and practical applications. The pattern of the human iris differs from person to person, even between monocular twins. This paper proposes a modified iris localization method and normalization method. In the iris localization after invert the iris image edges are detected by using the Canny edge detection. The average of the edge points as taken as coarse center of the pupil. Using coarse center of pupil, Circular Hough Transform method is applied to determine the location of the iris boundaries. The normalization is used for converting the circular iris into rectangular form with fixed dimensions. The proposed method is for non-concentric iris. In this paper 2D Log-Gabor Filters are used for feature extraction and hamming distance is used for matching. The experimental result shows the proposed method has an encouraging performance.

Dynamic ROI extraction algorithm for palmprints

Region of Interest (ROI) extraction is an important task for palmprint identification. Earlier reported works used fixed size ROI for the recognition of palmprints. When the fixed size ROI is used the palm area taken up for recognition is less compared to dynamic ROI extraction. The proposed algorithm focuses on extraction of maximum possible ROI compared to existing fixed and dynamic ROI extraction techniques [7, 19]. The experimental results demonstrate that the proposed approach extracts better ROI on three databases, 1. The PolyU Palmprint Database, 2. CASIA Palmprint Image Database and 3. IIT Delhi Palmprint Database, when compared to the existing fixed size and dynamic size ROI extraction techniques.

Vein Pattern Indexing Using Texture and Hierarchical Decomposition of Delaunay Triangulation

In biometric identification systems, the identity corresponding to the query image is determined by comparing it against all images in the database. This exhaustive matching process increases the response time and the number of false positives of the system; therefore, an effective mechanism is essential to select a small collection of candidates to which the actual matching process is applied. This paper presents an efficient indexing algorithm for vein pattern databases to improve the search speed and accuracy of identification. In this work, we generate a binary code for each image using texture information. A hierarchical decomposition of Delaunay triangulation based approach for minutiae is proposed and used with binary code to narrow down the search space of the database. Experiments are conducted on two vein pattern databases, and the results show that, while maintaining 100% Hit Rate, the proposed method achieves lower penetration rate than what existing methods achieve.

A Bio-cryptosystem for Fingerprints Using Delaunay Neighbor Structures(DNS) and Fuzzy Commitment Scheme

The emergence of biometrics and it’s widespread use in authentication applications made template protection in biometrics an important task to be considered in recent years. In this paper we propose a fingerprint bio-cryptosystem using fuzzy commitment scheme. We constructed Delaunay Neighbor Structures(DNS) from fingerprint minutiae points. Then a bit string representation of DNSs was developed. Bose, Chaudhuri, and Hocquenghem(BCH) error correction code is used along with bit string in the fuzzy commitment scheme to generate a secure template. During decoding phase, BCH decoding is performed to get the codeword. The EER obtained for proposed method on FVC 2002 DB1, DB2 and DB3 are 1.43%, 1.79%, and 5.89% respectively. This shows the credibility of the proposed method.

Palmprint identification and verification based on wide principal lines through dynamic ROI

In this paper, a novel palmprint identification and verification algorithm is proposed based on wide principal lines through dynamic ROI. Region of interest ROI extraction is an important task for palmprint identification. Earlier reported works used fixed size ROI for the recognition of palmprints. When the fixed size ROI is used the palm area taken up for recognition is less compared to dynamic ROI extraction. The proposed algorithm focuses on extraction of maximum possible ROI. A set of wide principal line extractors are devised. Later these wide principal line extractors are used to extract the wide principal lines from dynamic ROI. A two stage palmprint identification algorithm is proposed based on wide principal lines. The experimental results demonstrate that the proposed approach extracts better ROI on the PolyUPalmprint Database when compared to the existing fixed size and dynamic size ROI extraction techniques. The experimental results for the verification and identification on PolyUPalmprint Database show that the discrimination of wide principal lines is also strong.

Classification of Extended Delaunay Triangulation for Fingerprint Indexing

In this paper, we propose an efficient indexing mechanism for the fingerprints based on minutiae triplets. First, we compute the Delaunay triangulation for each fingerprint using the minutiae features. Further, we define a novel representation for the fingerprint named extended triangle set, which is very tolerant to missing minutiae. The defined extended triangle set is an extension of the Delaunay triangulation and is used in combination with a classification approach to narrow down the search space of a fingerprint database. Experiments are conducted on different Fingerprint Verification Competition (FVC) databases and the results show that, while maintaining high hit rate the proposed method achieves lower penetration rate than existing methods.

Digital Watermarking Based on Magic Square and Ridgelet Transform Techniques

This paper proposes two algorithms for embedding and extraction of the watermark into the cover image based on magic square and ridgelet transform techniques. Spread-spectrum communication systems use the spread sequences that have good correlation properties. Magic square technique is used as a spread-spectrum technique to spread the watermark. Ridgelet transform is the next-generation wavelets as it is effective through line singularities characteristic. Ridgelet transform generates sparse image representation where the most significant coefficient represents the most energetic direction of an image with straight edges. The experiments indicated that these algorithms enabled the cover images to have the good invisibility and made them robust to the general image compression attacks such as JPEG, GIF.