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Feature Extraction Methods for Palmprint Recognition: A Survey and Evaluation by Lunke Fei; Guangming Lu; Wei Jia; Shaohua Teng; David Zhang is a Engineering article available to read on EtoBox.

What is Feature Extraction Methods for Palmprint Recognition: A Survey and Evaluation about?

Palmprint processes a number of unique features for reliable personal recognition. However, different types of palmprint images contain different dominant features. Instead, only some features of the palmprint are visible in a palmprint image, whereas the other features may not be notable. For example, the low-resolution palmprint image has visible principal lines and wrinkles. By contrast, the high-resolution palmprint image contains clear ridge patterns and minutiae points. In addition, the three dimensional (3-D) palmprint image possesses curvatures of the palmprint surface. So far, there is no work to summarize the feature extraction of different types of palmprint images. In this paper, we have an aim to completely study the feature extraction and recognition of palmprint. We propose to use a unified framework to classify palmprint images into four categories: 1) the contact-based; 2) contactless; 3) high-resolution; and 4) 3-D palmprint images. Then, we analyze the motivations and theories of the representative extraction and matching methods for different types of palmprint images. Finally, we compare and test the state-of-the-art methods via the widely used palmprint databa

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Author

Lunke Fei; Guangming Lu; Wei Jia; Shaohua Teng; David Zhang

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Published

2019

Language

EN

Field

Engineering (Physical Sciences)