3D Palmprint Recognition Using Dempster-Shafer Fusion Theory

Ni, Jianyun; Luo, Jing; Liu, Wubin

doi:10.1155/2015/252086

Cited by 14 publications

(3 citation statements)

References 21 publications

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“…For a long time, palmprint recognition was only based on features extracted from 2D optical images, which allow having quick and accurate systems [8], but can be easily forged [9]. In the last decade, however, a new modality for achieving 3D palmprint images, based on structured light imaging [9], [10], was set up and a wide research activity was dedicated to develop methods for extracting 3D features [11]- [16]. A possible limitation of these approaches could be because 3-D optical images provide information on the external skin surface only.…”

Section: Introductionmentioning

confidence: 99%

A Feasible 3D Ultrasound Palmprint Recognition System for Secure Access Control Applications

Iula

Micucci

2021

IEEE Access

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Biometric recognition systems based on 3D palmprint captured with optical technology have been widely investigated in the last decade; however, they can provide information about the external skin surface only. This limit can be overcome by Ultrasound, which allows gaining information on the depth of palm lines and can verify the liveness of the sample, making the recognition systems very hard to fake. In this work, a feasible palmprint recognition system based on 3D ultrasound images is proposed. Unlike previous wet setups, the coupling between probe and human is realized through a gel pad, which permits a comfortable and precise positioning of the hand by the user. Collected 3D images are processed to generate 2D palmprint images at various under-skin depths. 2D features are then extracted from these images, experimenting with different procedures, and are merged to define a 3D template that contains lines' depth information. Recognition performances were evaluated by performing verification and identification experiments on a home-made database composed of 423 samples from 55 volunteers. An EER rate of 0.36% and an identification accuracy of 100% are obtained. The suitability of the proposed system in secure access control applications is finally discussed.

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Section: Introductionmentioning

confidence: 99%

A Feasible 3D Ultrasound Palmprint Recognition System for Secure Access Control Applications

Iula

Micucci

2021

IEEE Access

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“…Earlier, DS theory based combination has been applied on different fields like handwritten digit recognition [41], skin detection [42], 3D palm print recognition [43] among other pattern recognition domains.…”

Section: Dempster-shafer Theory Of Evidencementioning

confidence: 99%

A Study of Different Classifier Combination Approaches for Handwritten Indic Script Recognition

et al. 2018

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Script identification is an essential step in document image processing especially when the environment is multi-script/multilingual. Till date researchers have developed several methods for the said problem. For this kind of complex pattern recognition problem, it is always difficult to decide which classifier would be the best choice. Moreover, it is also true that different classifiers offer complementary information about the patterns to be classified. Therefore, combining classifiers, in an intelligent way, can be beneficial compared to using any single classifier. Keeping these facts in mind, in this paper, information provided by one shape based and two texture based features are combined using classifier combination techniques for script recognition (word-level) purpose from the handwritten document images. CMATERdb8.4.1 contains 7200 handwritten word samples belonging to 12 Indic scripts (600 per script) and the database is made freely available at https://code.google.com/p/cmaterdb/. The word samples from the mentioned database are classified based on the confidence scores provided by Multi-Layer Perceptron (MLP) classifier. Major classifier combination techniques including majority voting, Borda count, sum rule, product rule, max rule, Dempster-Shafer (DS) rule of combination and secondary classifiers are evaluated for this pattern recognition problem. Maximum accuracy of 98.45% is achieved with an improvement of 7% over the best performing individual classifier being reported on the validation set.

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“…However, accuracy was not achieved in the above-stated algorithms. To average the equal error rate in [ 21 ], Dempster-Shafer fusion theory was applied to unique features using mean curvature features.…”

Section: Related Workmentioning

confidence: 99%

Palm‐Print Pattern Matching Based on Features Using Rabin‐Karp for Person Identification

Kanchana

Balakrishnan²

2015

The Scientific World Journal

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Palm-print based individual identification is regarded as an effectual method for identifying persons with high confidence. Palm-print with larger inner surface of hand contains many features such as principle lines, ridges, minutiae points, singular points, and textures. Feature based pattern matching has faced the challenge that the spatial positional variations occur between the training and test samples. To perform effective palm-print features matching, Rabin-Karp Palm-Print Pattern Matching (RPPM) method is proposed in this paper. With the objective of improving the accuracy of pattern matching, double hashing is employed in RPPM method. Multiple patterns of features are matched using the Aho-Corasick Multiple Feature matching procedure by locating the position of the features with finite set of bit values as an input text, improving the cumulative accuracy on hashing. Finally, a time efficient bit parallel ordering presents an efficient variation on matching the palm-print features of test and training samples with minimal time. Experiment is conducted on the factors such as pattern matching efficiency rate, time taken on multiple palm-print feature matching efficiency, and cumulative accuracy on hashing.

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3D Palmprint Recognition Using Dempster-Shafer Fusion Theory

Cited by 14 publications

References 21 publications

A Feasible 3D Ultrasound Palmprint Recognition System for Secure Access Control Applications

A Feasible 3D Ultrasound Palmprint Recognition System for Secure Access Control Applications

A Study of Different Classifier Combination Approaches for Handwritten Indic Script Recognition

Palm‐Print Pattern Matching Based on Features Using Rabin‐Karp for Person Identification

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