Author(s)

Danping Ge, Xinwu Chen, Youchao Tu

School of Physics and Electronic Engineering, Xinyang Normal University, Xinyang, China.

In the global environment of COVID-19 outbreak, contactless biometric identification technology improves the security of services. As an important biometric recognition method, one of the important aspects of palmprint recognition is feature extraction. In order to perform palmprint image feature extraction and recognition accurately and efficiently, this paper proposes a wavelet transform palmprint image retrieval system. The palmprint image is extracted from the region of interest, and the wavelet transform is used to decompose the palmprint region of interest into third-order decomposition and fourth-order decomposition for feature vector extraction, and the distance criterion is used to transform different decomposition scales and filter combinations for image similarity retrieval. The experimental results show that the combination of pkva and pkva filters with four scale transformations on ROI images has the highest retrieval rate of about 0.94, and the feature vectors are a combination of absolute mean, kurtosis, variance, roughness and smoothness.

Palmprint Image Retrieval, Wavelet Transform, Region of Interest (ROI), Feature Extraction

Ge, D.P., Chen, X.W. and Tu, Y.C. (2022) Wavelet Transform ROI Palmprint Image Retrieval System. Open Access Library Journal, 9, 1-10. doi: 10.4236/oalib.1108986.