Palm Print Based Person Identification
26 Feb 2015-pp 781-785
TL;DR: The experimentation for this project is done using PolyU palm print Database to acquire more discriminative information and increase the anti spoof capability of palm print.
Abstract: Palm print is a unique and reliable biometric characteristic with high usability. With the increasing demand of highly accurate and robust palm print authentication system, multispectral imaging has been employed to acquire more discriminative information and increase the anti spoof capability of palm print. The experimentation for this project is done using PolyU palm print Database. Palm print images were collected from 250volunteers, including 195 males and 55 females. The palm print features are extracted using stockwell transform. Some of the significant results have accuracy of 99% and precision 91%.
Citations
More filters
TL;DR: This study presents a nonfiducial PPG-based subject authentication system that achieved an average authentication accuracy of 99.3% using a 15 sec frame length with the augmented multiband approach.
Abstract: Nowadays, there is a global change in lifestyle that is moving more toward the use of e-services and smart devices which necessitate the verification of user identity. Different organizations have put into place a range of technologies, hardware, and/or software to authenticate users using fingerprints, iris recognition, and so forth. However, cost and reliability are significant limitations to the use of such technologies. This study presents a nonfiducial PPG-based subject authentication system. In particular, the photoplethysmogram (PPG) signal is first filtered into four signals using the discrete wavelet transform (DWT) and then segmented into frames. Ten simple statistical features are extracted from the frame of each signal band to compose the feature vector. Augmenting the feature vector with the same features extracted from the 1st derivative of the corresponding signal is investigated, along with different fusion approaches. A support vector machine (SVM) classifier is then employed for the purpose of identity authentication. The proposed authentication system achieved an average authentication accuracy of 99.3% using a 15 sec frame length with the augmented multiband approach.
9 citations
TL;DR: The experiment reveals that hand radiographs contain biometric information that can be used to identify humans in disaster victim identification and indicates that the proposed approach is significantly effective than conventional methods for the person authentication using hand radiograph based human authentication.
Abstract: Biometric radiographs have gained importance in recent times owing to the rise in crime and disaster incidents. In recent times, authentication and identification of a person has become an essential part of most of the computer vision automation systems. Conventional fingerprint, iris, face, palm prints fail to recognize the human when the external biometric parts have been damaged due to rashes, wounds, and severe burning. Security, robustness, privacy, and non-forgery are the critical aspects of any person authentication system. In such situations, identification based on radiographs of the skull, hand, and teeth are effective replacement methods. In this paper, a novel forensic hand radiograph based human authentication is proposed using a deep neural network. Three-layered convolutional deep neural network architecture is used for the feature extraction of hand radiographs and for recognition; KNN and SVM classifiers are used. As a part of the experimentation, a total of 750 hand radiographs acquired from 150 subjects of different age groups, professions, and gender are considered. The performance of the algorithm is evaluated based on cross-validation accuracy by varying striding pixels, polling window size, kernel size, and the number of filters. Our experiment reveals that hand radiographs contain biometric information that can be used to identify humans in disaster victim identification. The experimental study also indicates that the proposed approach is significantly effective than conventional methods for the person authentication using hand radiographs.
7 citations
Cites background from "Palm Print Based Person Identificat..."
...Presently, the biometric identification systems are based on static features like face [1], iris [2], palm print [3], voice [4] and fingerprint impression [5] of the user, which mostly remains unchanged over time....
[...]
01 Sep 2016
TL;DR: A hybrid approach for palm print recognition is proposed using a combination of three different approaches of Image processing to facilitate the dynamic selection of palm print pattern to match it by combining various global and local features of a palm print in a hierarchical way.
Abstract: The major issues that involve in identifying palm print are the search for the templates in the palm print database that best matches with the test sample from input. Here the fundamental to be solved are to select similar features of palm that are needs to be matched. The different feature of palm print that are able to discriminate them from each other must show a huge divergence between different users samples and few divergence between same user samples. For verification process principal lines and datum points are successfully used as an important palm print features, but some other features that are associated with a palm print are delta point features, geometry features, minutiae features and wrinkle features. By using the existing techniques, we propose a distinct scheme to facilitate the dynamic selection of palm print pattern to match it by combining various global and local features of a palm print in a hierarchical way. Our palm print matching system will operate in two steps, enrollment of user and verification of user. In first step that is enrollment; several palm print samples are obtained by a user to store them as templates in the system. Palm print scanner is used to capture the samples which then pass through preprocessing and feature extraction to create the templates which then stored in predefined palm print database. In second and final step, the palm print scanner is used to capture the fresh palm print sample of user. Then the captured palm print sample again passes through preprocessing and feature extraction. These extracted features of a user are compared with existing templates in the database to verify the identity of the user. In this paper, we are proposing a hybrid approach for palm print recognition using a combination of three different approaches of Image processing.
5 citations
01 Jan 2017
TL;DR: An efficient palmprint matching algorithm using nearest neighbor minutiae quadruplets improves the matching accuracy at nearest neighbors by discarding scope of the global matching on false minutia points.
Abstract: Palmprint recognition is a variant of fingerprint matching as both the systems share almost similar matching criteria and the minutiae feature extraction methods. However, there is a performance degradation with palmprint biometrics because of the failure of extracting genuine minutia points from the region of highly distorted ridge information with huge data. In this paper, we propose an efficient palmprint matching algorithm using nearest neighbor minutiae quadruplets. The representation of minutia points in the form of quadruplets improves the matching accuracy at nearest neighbors by discarding scope of the global matching on false minutia points. The proposed algorithm is evaluated on publicly available high resolution palmprint standard databases, namely, palmprint benchmark data sets (FVC ongoing) and Tsinghua palmprint database (THUPALMLAB). The experimental results demonstrate that the proposed palmprint matching algorithm achieves the state-of-the-art performance.
3 citations
TL;DR: This system proposes a KNN classifier to match the current palm print with the existing dataset, which produces a better result than other matching techniques.
3 citations
References
More filters
TL;DR: In this review, the emerging role of the wavelet transform in the interrogation of the ECG is discussed in detail, where both the continuous and the discrete transform are considered in turn.
Abstract: The wavelet transform has emerged over recent years as a powerful time-frequency analysis and signal coding tool favoured for the interrogation of complex nonstationary signals. Its application to biosignal processing has been at the forefront of these developments where it has been found particularly useful in the study of these, often problematic, signals: none more so than the ECG. In this review, the emerging role of the wavelet transform in the interrogation of the ECG is discussed in detail, where both the continuous and the discrete transform are considered in turn.
794 citations
"Palm Print Based Person Identificat..." refers background in this paper
...It remove any isolated small blobs or holes on image....
[...]
TL;DR: Experimental results verify the validity of the proposed approaches in personal authentication using the template-matching and the backpropagation neural network to measure the similarity in the verification stage.
493 citations
"Palm Print Based Person Identificat..." refers methods in this paper
...First remove the noise from the image by using morphological operations [8]....
[...]
TL;DR: This paper proposes specific verification technology by making use of hand-based features by using the positive Boolean function (PBF) and the bootstrapping method to verify the identity of samples possessing confused hand shapes.
102 citations
"Palm Print Based Person Identificat..." refers background in this paper
...It remove any isolated small blobs or holes on image....
[...]
01 Oct 2011
TL;DR: This paper proposes a novel technique to extract palm-print features based on instantaneous-phase difference obtained using Stockwell transform of overlapping circular-strips and this palm-prints region is found to be robust to translation and rotation on the scanner.
Abstract: This paper proposes a novel technique to extract palm-print features based on instantaneous-phase difference obtained using Stockwell transform of overlapping circular-strips. The hand images are acquired using a low cost scanner. A procedure is proposed to classify hand images into either right or left hand based on their inherent characteristics and then the palm-print region from the hand image is extracted accordingly. This palm-print region is found to be robust to translation and rotation on the scanner. The proposed system is tested on IITK database of 549 images, CASIA database of 5239 images and PolyU database of 7751 images. The system performs with 100% correct recognition rate (CRR) and equal error rate (EER) less than 1% for all the databases.
41 citations
"Palm Print Based Person Identificat..." refers background in this paper
...It remove any isolated small blobs or holes on image....
[...]